diff --git a/.github/workflows/documentation.yml b/.github/workflows/documentation.yml new file mode 100644 index 0000000..47edd07 --- /dev/null +++ b/.github/workflows/documentation.yml @@ -0,0 +1,47 @@ +name: documentation + +on: + pull_request: + push: + branches: + - main + release: + types: + - published + +permissions: + contents: write + +jobs: + docs: + runs-on: ubuntu-latest + steps: + - name: Checkout + uses: actions/checkout@v4 + with: + fetch-depth: 100 + persist-credentials: false + + - name: Setup Python + uses: actions/setup-python@v5 + with: + python-version: "3.11" + + - name: Install dependencies + shell: bash -l {0} + run: | + python -m pip install --upgrade pip + python -m pip install -r requirements-dev.txt + + - name: Create docs + shell: bash -l {0} + run: make html + + - name: Deploy to GitHub Pages + uses: peaceiris/actions-gh-pages@v4 + if: ${{ github.event_name == 'push' && github.ref == 'refs/heads/main' }} + with: + publish_branch: gh-pages + github_token: ${{ secrets.GITHUB_TOKEN }} + publish_dir: ./docs/_build/html/ + force_orphan: true diff --git a/.github/workflows/linux.yml b/.github/workflows/linux.yml new file mode 100644 index 0000000..7448a71 --- /dev/null +++ b/.github/workflows/linux.yml @@ -0,0 +1,142 @@ +name: linux + +# Only build PRs, the main branch, and releases. +on: + pull_request: + push: + branches: + - main + release: + types: + - published + schedule: + - cron: "14 14 20 * *" + +# Use bash by default in all jobs +defaults: + run: + # Using "-l {0}" is necessary for conda environments to be activated + # But this breaks on MacOS if using actions/setup-python: + # https://github.com/actions/setup-python/issues/132 + shell: bash + +# Cancel any previous run of the test job. +concurrency: + group: ${{ github.workflow }}-${{ github.ref }} + cancel-in-progress: true + +jobs: + test: + + name: basic + runs-on: ubuntu-latest + + steps: + + # Checks-out your repository under $GITHUB_WORKSPACE + - name: Checkout + uses: actions/checkout@v4 + with: + # Need to fetch more than the last commit so that setuptools-scm can + # create the correct version string. If the number of commits since + # the last release is greater than this, the version still be wrong. + # Increase if necessary. + fetch-depth: 100 + # The GitHub token is preserved by default but this job doesn't need + # to be able to push to GitHub. + persist-credentials: false + + # Need the tags so that setuptools-scm can form a valid version number + - name: Fetch git tags + run: git fetch origin 'refs/tags/*:refs/tags/*' + + - name: Setup Python + uses: actions/setup-python@v5 + with: + python-version: "3.11" + + - name: Install dependencies + shell: bash -l {0} + run: | + python -m pip install --upgrade pip + python -m pip install -r requirements-dev.txt + + - name: Flake8 + shell: bash -l {0} + run: flake8 docs/conf.py setup.py resmda/ tests/ + + - name: Test with pytest + shell: bash -l {0} + run: | + python -m pip install . + pytest --cov=resmda + + deploy: + needs: test + name: Deploy to PyPI + runs-on: ubuntu-latest + # Only from the origin repository, not forks; only main and tags. + if: github.repository_owner == 'tuda' && (github.ref == 'refs/heads/main' || startsWith(github.ref, 'refs/tags/')) + + steps: + # Checks-out your repository under $GITHUB_WORKSPACE + - name: Checkout + uses: actions/checkout@v4 + with: + # Need to fetch more than the last commit so that setuptools-scm can + # create the correct version string. If the number of commits since + # the last release is greater than this, the version will still be + # wrong. Increase if necessary. + fetch-depth: 100 + # The GitHub token is preserved by default but this job doesn't need + # to be able to push to GitHub. + persist-credentials: false + + # Need the tags so that setuptools-scm can form a valid version number + - name: Fetch git tags + run: git fetch origin 'refs/tags/*:refs/tags/*' + + - name: Setup Python + uses: actions/setup-python@v5 + with: + python-version: "3.11" + + - name: Install dependencies + run: | + python -m pip install --upgrade pip + python -m pip install build setuptools-scm + + - name: Build source and wheel distributions + if: github.ref == 'refs/heads/main' + run: | + # Change setuptools-scm local_scheme to "no-local-version" so the + # local part of the version isn't included, making the version string + # compatible with Test PyPI. + sed --in-place 's/"root"/"local_scheme":"no-local-version","root"/g' setup.py + + - name: Build source and wheel distributions + run: | + # Build source and wheel packages + python -m build + echo "" + echo "Generated files:" + ls -lh dist/ + + - name: Publish to Test PyPI + if: success() + uses: pypa/gh-action-pypi-publish@release/v1 + with: + user: __token__ + password: ${{ secrets.TEST_PYPI_PASSWORD }} + repository_url: https://test.pypi.org/legacy/ + # Allow existing releases on test PyPI without errors. + # NOT TO BE USED in PyPI! + skip_existing: true + + - name: Publish to PyPI + # Only for releases + if: success() && github.event_name == 'release' + uses: pypa/gh-action-pypi-publish@release/v1 + with: + user: __token__ + password: ${{ secrets.PYPI_PASSWORD }} diff --git a/.gitignore b/.gitignore index 3c51f62..a53eba5 100644 --- a/.gitignore +++ b/.gitignore @@ -1,104 +1,22 @@ -# Byte-compiled / optimized / DLL files +# Directories and file types __pycache__/ -*.py[cod] -# C and Fortran extensions -*.so -*.dylib -*.dll -*.slo -*.lo -*.o -*.obj -*.mod -*.smod -*.lai -*.la -*.a -*.lib -*.exe -*.out -*.app - -# Distribution / packaging -.Python -env/ -build/ -develop-eggs/ -dist/ -downloads/ -eggs/ -.eggs/ -lib/ -lib64/ -parts/ -sdist/ -var/ -*.egg-info/ -.installed.cfg -*.egg - -# PyInstaller -# Usually these files are written by a python script from a template -# before PyInstaller builds the exe, so as to inject date/other infos into it. -*.manifest -*.spec - -# Installer logs -pip-log.txt -pip-delete-this-directory.txt - -# Unit test / coverage reports -htmlcov/ -.tox/ -.coverage -.coverage.* -.cache -nosetests.xml -coverage.xml -*,cover - -# Translations -*.mo -*.pot - -# Django stuff: -*.log - -# Sphinx documentation +# Sphinx docs/_build/ +docs/api/resmda* +docs/savefig/ +docs/gallery/* -# PyBuilder -target/ - -# DotEnv configuration -.env - -# Database -*.db -*.rdb - -# Pycharm -.idea - -# TeX/LaTeX -*.aux -*.bbl -*.blg -*.synctex.gz -*.xwm - -# IPython NB Checkpoints -.ipynb_checkpoints/ - -# exclude compiled binaries -bin/ +# Pytest and coverage related +htmlcov +.coverage +.pytest_cache/ -# exclude data from source control by default -/data/external -/data/interim -/data/processed -/data/raw +# setuptools_scm +resmda/version.py -# exclude external models from source control -/src/external/ +# Build related +.eggs/ +build/ +dist/ +resmda.egg-info/ diff --git a/AUTHORS.md b/AUTHORS.md deleted file mode 100644 index adf951e..0000000 --- a/AUTHORS.md +++ /dev/null @@ -1,12 +0,0 @@ -Credits -======= - -Project Lead ----------------- - -* tuda-geo - -Project Contributors ------------- - -None. diff --git a/LICENSE b/LICENSE index 4fca458..261eeb9 100644 --- a/LICENSE +++ b/LICENSE @@ -1,29 +1,201 @@ -BSD License - -Copyright (c) 2024, tuda-geo -All rights reserved. - -Redistribution and use in source and binary forms, with or without modification, -are permitted provided that the following conditions are met: - -* Redistributions of source code must retain the above copyright notice, this - list of conditions and the following disclaimer. - -* Redistributions in binary form must reproduce the above copyright notice, this - list of conditions and the following disclaimer in the documentation and/or - other materials provided with the distribution. - -* Neither the name of DA-EM-CCS nor the names of its - contributors may be used to endorse or promote products derived from this - software without specific prior written permission. - -THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND -ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED -WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. -IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, -INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, -BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, -DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY -OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE -OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED -OF THE POSSIBILITY OF SUCH DAMAGE. + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. 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We also recommend that a + file or class name and description of purpose be included on the + same "printed page" as the copyright notice for easier + identification within third-party archives. + + Copyright [yyyy] [name of copyright owner] + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. diff --git a/MANIFEST.in b/MANIFEST.in new file mode 100644 index 0000000..98bf66a --- /dev/null +++ b/MANIFEST.in @@ -0,0 +1,11 @@ +prune docs +prune tests +prune examples +prune .github +exclude MANIFEST.in +exclude Makefile +exclude requirements.txt +exclude requirements-dev.txt +exclude setup.cfg +exclude .gitignore +exclude .coveragerc diff --git a/Makefile b/Makefile new file mode 100644 index 0000000..f262c3b --- /dev/null +++ b/Makefile @@ -0,0 +1,52 @@ +help: + @echo "Commands:" + @echo "" + @echo " install install in editable mode" + @echo " dev-install install in editable mode with dev requirements" + @echo " pytest run the test suite and report coverage" + @echo " flake8 style check with flake8" + @echo " html build docs (update existing)" + @echo " html-noplot as above, without gallery" + @echo " html-clean build docs (new, removing any existing)" + @echo " preview renders docs in Browser" + @echo " linkcheck check all links in docs" + @echo " clean clean up all generated files" + @echo "" + +install: + python -m pip install --no-build-isolation --no-deps -e . + +dev-install: + python -m pip install -r requirements-dev.txt && python -m pip install --no-build-isolation --no-deps -e . + +.ONESHELL: +pytest: + rm -rf .coverage htmlcov/ .pytest_cache/ + pytest --cov=resmda + coverage html + +flake8: + flake8 docs/conf.py setup.py resmda/ tests/ examples/ + +html: + cd docs && make html + +html-noplot: + cd docs && make html-noplot + +html-clean: + cd docs && rm -rf api/resmda* gallery/*/ _build/ my*.json my*.txt && make html + +preview: + xdg-open docs/_build/html/index.html + +linkcheck: + cd docs && make linkcheck + +clean: + python -m pip uninstall resmda -y + rm -rf build/ dist/ .eggs/ resmda.egg-info/ resmda/version.py # build + rm -rf */__pycache__/ */*/__pycache__/ # python cache + rm -rf .coverage htmlcov/ .pytest_cache/ # tests and coverage + rm -rf docs/gallery/* docs/gallery/*.zip docs/_build/ docs/api/resmda* # docs + rm -rf docs/savefig diff --git a/README.md b/README.md deleted file mode 100644 index 2e28c61..0000000 --- a/README.md +++ /dev/null @@ -1,29 +0,0 @@ -da-em-ccs -============================== - -Data assimilation with EM for CCS - -Project Organization --------------------- - - . - ├── AUTHORS.md - ├── LICENSE - ├── README.md - ├── bin - ├── config - ├── data - │   ├── external - │   ├── interim - │   ├── processed - │   └── raw - ├── docs - ├── notebooks - ├── reports - │   └── figures - └── src - ├── data - ├── external - ├── models - ├── tools - └── visualization diff --git a/README.rst b/README.rst new file mode 100644 index 0000000..4e8842c --- /dev/null +++ b/README.rst @@ -0,0 +1,13 @@ +``resmda`` - Simple Reservoir Modeller with ESMDA +================================================= + +A simple 2D reservoir simulator and a straight-forward implementation of the +basic *Ensemble smoother with multiple data assimilation* (ESMDA) algorithm as +presented by Emerick and Reynolds, 2013. + +- **Documentation:** https://tuda-geo.github.io/resmda +- **Source Code:** https://github.com/tuda-geo/resmda +- **Bug reports:** https://github.com/tuda-geo/resmda/issues + + +Available through pip: ``pip install resmda``. diff --git a/docs/.gitkeep b/docs/.gitkeep deleted file mode 100644 index e69de29..0000000 diff --git a/config/.gitkeep b/docs/.nojekyll similarity index 100% rename from config/.gitkeep rename to docs/.nojekyll diff --git a/docs/Makefile b/docs/Makefile new file mode 100644 index 0000000..469256b --- /dev/null +++ b/docs/Makefile @@ -0,0 +1,23 @@ +# Command line options. +SPHINXOPTS = +SPHINXBUILD = sphinx-build +SPHINXPROJ = resmda +SOURCEDIR = . +BUILDDIR = _build + +# Will also be triggered if "make" is provided without argument. +help: + @$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) + +.PHONY: help Makefile + +html-noplot: + $(SPHINXBUILD) -D plot_gallery=0 -b html $(ALLSPHINXOPTS) $(SOURCEDIR) $(BUILDDIR)/html + +linkcheck-noplot: + $(SPHINXBUILD) -D plot_gallery=0 -b linkcheck $(ALLSPHINXOPTS) $(SOURCEDIR) $(BUILDDIR)/html + +# Catch-all target: route all unknown targets to Sphinx using the new +# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS). +%: Makefile + @$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) diff --git a/docs/conf.py b/docs/conf.py new file mode 100644 index 0000000..a1c509f --- /dev/null +++ b/docs/conf.py @@ -0,0 +1,118 @@ +import time +import warnings +from resmda import __version__ +from sphinx_gallery.sorting import FileNameSortKey + +# ==== 1. Extensions ==== + +# Load extensions +extensions = [ + # 'sphinx.ext.autodoc', + 'numpydoc', + 'sphinx_design', + 'sphinx.ext.intersphinx', + # 'sphinx.ext.autosummary', + 'sphinx.ext.mathjax', + 'sphinx.ext.viewcode', + 'sphinx.ext.todo', + 'sphinx_gallery.gen_gallery', + 'sphinx_automodapi.automodapi', + 'matplotlib.sphinxext.plot_directive', + 'IPython.sphinxext.ipython_console_highlighting', + 'IPython.sphinxext.ipython_directive', +] +autosummary_generate = True +add_module_names = True +add_function_parentheses = False + +# Numpydoc settings +numpydoc_show_class_members = False +# numfig = True +# numfig_format = {'figure': 'Figure %s:'} +# Make numpydoc to generate plots for example sections +numpydoc_use_plots = True + +# Todo settings +todo_include_todos = True + +# Sphinx gallery configuration +sphinx_gallery_conf = { + 'examples_dirs': ['../examples', ], + 'gallery_dirs': ['gallery', ], + 'capture_repr': ('_repr_html_', '__repr__'), + # Patter to search for example files + "filename_pattern": r"\.py", + # Sort gallery example by file name instead of number of lines (default) + "within_subsection_order": FileNameSortKey, + # Remove the settings (e.g., sphinx_gallery_thumbnail_number) + 'remove_config_comments': True, + # Show memory + 'show_memory': True, + # Custom first notebook cell + 'first_notebook_cell': '%matplotlib notebook', +} + +# https://github.com/sphinx-gallery/sphinx-gallery/pull/521/files +# Remove matplotlib agg warnings from generated doc when using plt.show +warnings.filterwarnings("ignore", category=UserWarning, + message='Matplotlib is currently using agg, which is a' + ' non-GUI backend, so cannot show the figure.') + +# Intersphinx configuration +intersphinx_mapping = { + "numpy": ("https://numpy.org/doc/stable", None), + "scipy": ("https://docs.scipy.org/doc/scipy", None), +} + +# ==== 2. General Settings ==== +description = "A simple 2D reservoir modeller plus ESMDA." + +# The templates path. +# templates_path = ['_templates'] + +# The suffix(es) of source filenames. +source_suffix = '.rst' + +# The master toctree document. +master_doc = 'index' + +# General information about the project. +project = 'resmda' +author = 'Dieter Werthmüller, Gabriel Serrao Seabra' +copyright = f'2024-{time.strftime("%Y")}, {author}' + +# |version| and |today| tags (|release|-tag is not used). +version = __version__ +release = __version__ +today_fmt = '%d %B %Y' + +# List of patterns to ignore, relative to source directory. +exclude_patterns = ['_build', '../tests'] + +# The name of the Pygments (syntax highlighting) style to use. +pygments_style = 'friendly' + +# ==== 3. HTML settings ==== +html_theme = 'pydata_sphinx_theme' +html_static_path = ['_static'] +# html_logo = '_static/empymod-logo.svg' +# html_favicon = '_static/favicon.ico' + +html_theme_options = { + "logo": { + "text": "resmda", + }, + "github_url": "https://github.com/tuda-geo/resmda", + # "use_edit_page_button": True, +} + +html_context = { + "github_user": "tuda-geo", + "github_repo": "resmda", + "github_version": "main", + "doc_path": "docs", +} + +html_use_modindex = True +html_file_suffix = '.html' +htmlhelp_basename = 'resmda' diff --git a/docs/index.rst b/docs/index.rst new file mode 100644 index 0000000..90d4398 --- /dev/null +++ b/docs/index.rst @@ -0,0 +1,24 @@ +.. _resmda-manual: + +#################### +resmda Documentation +#################### + +:Release: |version| +:Date: |today| +:Source: `github.com/tuda-geo/resmda `_ + +---- + +.. toctree:: + :hidden: + + manual/index + gallery/index + + +**TODOs** + +- Add tests +- Use this ``resmda`` to reproduce Geirs example +- Compare with existing esmda's diff --git a/docs/manual/about.rst b/docs/manual/about.rst new file mode 100644 index 0000000..4c3a9e6 --- /dev/null +++ b/docs/manual/about.rst @@ -0,0 +1,6 @@ +About +===== + +A simple 2D reservoir simulator and a straight-forward implementation of the +basic *Ensemble smoother with multiple data assimilation* (ESMDA) algorithm as +presented by Emerick and Reynolds, 2013. diff --git a/docs/manual/api.rst b/docs/manual/api.rst new file mode 100644 index 0000000..a9a6130 --- /dev/null +++ b/docs/manual/api.rst @@ -0,0 +1,26 @@ +API reference +============= + + +Data Assimilation +----------------- + +.. automodapi:: resmda.data_assimilation + :no-inheritance-diagram: + :no-heading: + + +Reservoir Simulator +------------------- + +.. automodapi:: resmda.reservoir_simulator + :no-inheritance-diagram: + :no-heading: + + +Utilities +--------- + +.. automodapi:: resmda.utils + :no-inheritance-diagram: + :no-heading: diff --git a/docs/manual/index.rst b/docs/manual/index.rst new file mode 100644 index 0000000..44b0c3b --- /dev/null +++ b/docs/manual/index.rst @@ -0,0 +1,18 @@ +.. _manual: + +########## +User Guide +########## + +:Release: |version| +:Date: |today| + +---- + +.. toctree:: + :maxdepth: 2 + :hidden: + + about + installation + api diff --git a/docs/manual/installation.rst b/docs/manual/installation.rst new file mode 100644 index 0000000..e31fe49 --- /dev/null +++ b/docs/manual/installation.rst @@ -0,0 +1,8 @@ +Installation +============ + +You can install resmda simply via ``pip``: + +.. code-block:: console + + pip install resmda diff --git a/examples/README.rst b/examples/README.rst new file mode 100644 index 0000000..71f2ff1 --- /dev/null +++ b/examples/README.rst @@ -0,0 +1,6 @@ +.. _sphx_glr_gallery: + +Gallery +======= + +TODO diff --git a/examples/example.py b/examples/example.py new file mode 100644 index 0000000..7f10e36 --- /dev/null +++ b/examples/example.py @@ -0,0 +1,185 @@ +r""" +Minimum example of resmda +========================= + +Data Assimilation using ESMDA in Reservoir Simulation +----------------------------------------------------- + +*Advanced Data Assimilation using Ensemble Smoother Multiple Data Assimilation +(ESMDA) in Reservoir Simulation.* + +$$ +m_j^a = m_j^f + C_{MD}^f (C_{DD}^f + \alpha_i C_D)^{-1} (d_{uc,j} - +d_j^f);\quad \text{for} \quad j=1, 2, \dots, N_e +$$ + +- Prior model: M (Ne, Nx, Ny) +- Prior data: D (Ne, Nt) +""" +import numpy as np +import matplotlib.pyplot as plt + +import resmda + +rng = np.random.default_rng(1848) + +# sphinx_gallery_thumbnail_number = 4 + +############################################################################### +# Model parameters +# ---------------- + +# Grid extension +nx = 25 +ny = 25 +nc = nx*ny + +# Permeabilities +perm_mean = 3.0 +perm_min = 0.5 +perm_max = 5.0 + +# ESMDA parameters +ne = 100 # Number of ensembles +# dt = np.logspace(-5, -3, 10) +dt = np.zeros(10)+0.0001 # Time steps (could be irregular, e.g., increasing!) +time = np.r_[0, np.cumsum(dt)] +nt = time.size + +# Assumed sandard deviation of our data +dstd = 0.5 + +# Observation location indices (should be well locations) +ox, oy = 1, 1 +# ox, oy = (1, 10, 20), (1, 20, 10) + +# Wells (if None, first and last cells are used with pressure 180 and 120) +# wells = np.array([[15, 10, 180], [55, 25, 120], [30, 7, 140]]) +wells = None + + +############################################################################### +# Create permeability maps for ESMDA +# ---------------------------------- +# +# We will create a set of permeability maps that will serve as our initial +# guess (prior). These maps are generated using a Gaussian random field and are +# constrained by certain statistical properties. + +# Get the model and ne prior models +RP = resmda.RandomPermeability(nx, ny, perm_mean, perm_min, perm_max) +perm_true = RP(1, random=rng) +perm_prior = RP(ne, random=rng) + + +# TODO: change scale in imshow to represent meters + +# QC covariance, reference model, and first two random models +fig, axs = plt.subplots(2, 2, constrained_layout=True) +axs[0, 0].set_title('Model') +im = axs[0, 0].imshow(perm_true.T, vmin=perm_min, vmax=perm_max) +axs[0, 1].set_title('Lower Covariance Matrix') +im2 = axs[0, 1].imshow(RP.cov, cmap='plasma') +axs[1, 0].set_title('Random Model 1') +axs[1, 0].imshow(perm_prior[0, ...].T, vmin=perm_min, vmax=perm_max) +axs[1, 1].set_title('Random Model 2') +axs[1, 1].imshow(perm_prior[1, ...].T, vmin=perm_min, vmax=perm_max) +fig.colorbar(im, ax=axs[1, :], orientation='horizontal', + label='Log of Permeability (mD)') +for ax in axs[1, :]: + ax.set_xlabel('x-direction') +for ax in axs[:, 0]: + ax.set_ylabel('y-direction') + + +############################################################################### +# Run the prior models and the reference case +# ------------------------------------------- + +# Instantiate reservoir simulator +RS = resmda.Simulator(nx, ny, wells=wells) + + +def sim(x): + """Custom fct to use exp(x), and specific dt & location.""" + return RS(np.exp(x), dt=dt, data=(ox, oy)) + + +# Simulate data for the prior and true fields +data_prior = sim(perm_prior) +data_true = sim(perm_true) +data_obs = rng.normal(data_true, dstd) + +# QC data and priors +fig, ax = plt.subplots(1, 1) +ax.set_title('Observed and prior data') +ax.plot(time, data_prior.T, color='.6', alpha=0.5) +ax.plot(time, data_true, 'ko', label='True data') +ax.plot(time, data_obs, 'C3o', label='Obs. data') +ax.legend() +ax.set_xlabel('Time (???)') +ax.set_ylabel('Pressure (???)') + + +############################################################################### +# ESMDA +# ----- + + +def restrict_permeability(x): + x[:] = np.clip(x, perm_min, perm_max) + + +perm_post, data_post = resmda.esmda( + model_prior=perm_prior, + forward=sim, + data_obs=data_obs, + sigma=dstd, + alphas=4, + data_prior=data_prior, + callback_post=restrict_permeability, + random=rng, +) + + +############################################################################### +# Posterior Analysis +# ------------------ +# +# After running ESMDA, it's crucial to analyze the posterior ensemble of +# models. Here, we visualize the first three realizations from both the prior +# and posterior ensembles to see how the models have been updated. + +# Plot posterior +fig, ax = plt.subplots(1, 3, figsize=(12, 5)) +ax[0].set_title('Prior Mean') +ax[0].imshow(perm_prior.mean(axis=0).T) +ax[1].set_title('Post Mean') +ax[1].imshow(perm_post.mean(axis=0).T) +ax[2].set_title('"Truth"') +ax[2].imshow(perm_true.T) + + +############################################################################### +# Observing the monitored pressure at cell (1,1) for all realizations and the +# reference case, we can see that the ensemble of models after the assimilation +# steps (in blue) is closer to the reference case (in red) than the prior +# ensemble (in gray). This indicates that the ESMDA method is effectively +# updating the models to better represent the observed data. + + +# Compare posterior to prior and observed data +fig, ax = plt.subplots(1, 1) +ax.set_title('Prior and posterior data') +ax.plot(time, data_prior.T, color='.6', alpha=0.5) +ax.plot(time, data_post.T, color='C0', alpha=0.5) +ax.plot(time, data_true, 'ko') +ax.plot(time, data_obs, 'C3o') +ax.set_xlabel('Time (???)') +ax.set_ylabel('Pressure (???)') + +plt.show() + +############################################################################### + +resmda.Report() diff --git a/notebooks/ESMDA.ipynb b/notebooks/ESMDA.ipynb deleted file mode 100644 index 83acdf4..0000000 --- a/notebooks/ESMDA.ipynb +++ /dev/null @@ -1,653 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Advanced Data Assimilation using Ensemble Smoother Multiple Data Assimilation (ESMDA) in Reservoir Simulation" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "This notebook demonstrates how to apply Ensemble Smoother Multiple Data Assimilation (ESMDA) in reservoir simulation. ESMDA is a data assimilation method that integrates observations and models to produce an improved estimate of the state of a system—in this case, a synthetic reservoir." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Objectives\n", - "Understand the ESMDA algorithm for data assimilation \n", - "\n", - "Explore the effect of different ensemble sizes, perturbations, and number of assimilation steps\n", - "\n", - "Analyze the convergence and effectiveness of the ESMDA method in a synthetic reservoir model\n", - "# Prerequisites\n", - "Knowledge of Python\n", - "\n", - "Familiarity with Data Assimilation Methods\n", - "\n", - "Understanding of Reservoir Simulation Models" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Understanding the reservoir simulator" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "from reservoir_simulator import ReservoirSim \n", - "import numpy as np\n", - "from scipy import stats\n", - "\n", - "\n", - "# Random number generator\n", - "rng = np.random.default_rng()" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "nx=25\n", - "ny=25\n", - "perm_field = np.ones(ny * ny) * 100 # Replace with your actual perm field\n", - "reservoir = ReservoirSim(nx=nx, ny=ny ,perm_field=perm_field)\n", - "pressure_history = reservoir.simulate()\n" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "pressure_history = pressure_history.reshape((pressure_history.shape[0], nx,ny))\n", - "plt.imshow(pressure_history[-1,:,:])\n" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[]" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.plot(pressure_history[:,1,1])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Create permeability maps for for ESMDA" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We will create a set of permeability maps that will serve as our initial guess (prior). These maps are generated using a Gaussian random field and are constrained by certain statistical properties.\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [], - "source": [ - "\n", - "#create 101 random permeability fields with mean 10 and std 1\n", - "##### USE GASPARHI COHN TO COMPUTE PERM\n", - "Ni = nx\n", - "Nj = ny\n", - "NGrid = Ni * Nj\n", - "Ne = 100\n", - "\n", - "def CalcHL(x0, x1, L, theta):\n", - " cosT = np.cos(theta)\n", - " sinT = np.sin(theta)\n", - " dx = x1[0] - x0[0]\n", - " dy = x1[1] - x0[1]\n", - "\n", - " dxRot = np.array([[cosT, -sinT], [sinT, cosT]]) @ np.array([[dx], [dy]])\n", - " dxFlat = dxRot.flatten()\n", - "\n", - " return np.sqrt((dxFlat[0]/L[0])**2 + (dxFlat[1]/L[1])**2)\n", - "\n", - "# Calc covariance between two gridblocks\n", - "def SphereFunction(x0, x1, L, theta, sigmaPr2):\n", - " hl = CalcHL(x0, x1, L, theta)\n", - "\n", - " if (hl > 1):\n", - " return 0\n", - " \n", - " return sigmaPr2 * (1.0 - 3.0/2.0*hl + (hl**3)/2)\n", - "\n", - "def GaspariCohnFunction(x0, x1, L, theta):\n", - " hl = CalcHL(x0, x1, L, theta)\n", - "\n", - " if (hl < 1):\n", - " return -(hl**5)/4. + (hl**4)/2. + (hl**3)*5./8. - (hl**2)*5./3. + 1.\n", - " if (hl >= 1 and hl < 2):\n", - " return (hl**5)/12. - (hl**4)/2. + (hl**3)*5./8. + (hl**2)*5./3. - hl*5 + 4 - (1/hl)*2./3.\n", - " \n", - " return 0" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Covariogram parameters \n", - "L = (10,10) \n", - "theta = 45 * np.pi/180 #degrees\n", - "sigmaPr2 = 1.0\n", - "csi = 0.99\n", - "\n", - " # convert index numeration to I J index\n", - "def IndexToIJ(index, ni, nj):\n", - " return ((index % ni) + 1, (index // ni) + 1)\n", - "\n", - "# Convert i J numeration to index\n", - "def IJToIndex(i,j,ni,nj):\n", - " return (i-1) + (j-1)*ni\n", - "\n", - "def BuildPermCovMatrix(Ni, Nj, L, theta, sigmaPr2):\n", - " Nmatrix = Ni * Nj\n", - " Cm = np.empty([Nmatrix, Nmatrix])\n", - " for index0 in range(Nmatrix):\n", - " I0 = IndexToIJ(index0,Ni,Nj)\n", - " for index1 in range(Nmatrix):\n", - " I1 = IndexToIJ(index1,Ni,Nj)\n", - " Cm[index0, index1] = SphereFunction(I0, I1, L, theta, sigmaPr2)\n", - " return Cm\n", - "\n", - "def PlotMatrix(matrix, title, axis, vmin=None, vmax=None):\n", - " axis.set_title(title)\n", - " return axis.imshow(matrix, cmap='viridis', vmin=vmin, vmax=vmax, aspect='auto')\n", - "\n", - "def PlotModelRealization(m, title, axis, vmin=None, vmax=None):\n", - " return PlotMatrix(m.reshape((Ni,Nj),order='F').T, title, axis, vmin, vmax)\n", - "# Generate the covariance matrix\n", - "\n", - "Cgrid = BuildPermCovMatrix(Ni, Nj, L, theta, sigmaPr2)\n", - "\n", - "fig, ax = plt.subplots()\n", - "im = PlotMatrix(Cgrid, 'CGrid', ax)\n", - "fig.colorbar(im, ax=ax)" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [], - "source": [ - "# Generate the ensembles\n", - "mpr = np.full((NGrid,1),3.0)\n", - "lCholesky = np.linalg.cholesky(Cgrid)\n", - "mList = []\n", - "for i in range(Ne+1): #+1 for the reference model\n", - " z = np.random.normal(size=(NGrid,1))\n", - " mList.append(mpr + lCholesky @ z)\n", - "\n", - "#MGridPrior remove the first to be the reference model\n", - "#clip the mList to min = 0.5 and max = 5 (related to MGrid values)\n", - "bound_max= 5\n", - "bound_min= 0.5\n", - "mList = np.clip(mList, bound_min, bound_max)\n", - "\n", - "mid_index = len(mList) // 2\n", - "# Set the middle element as the reference model\n", - "MReference = np.array(mList[mid_index])\n", - "# Slice the array to exclude the middle element\n", - "mList_without_middle = np.concatenate([mList[:mid_index], mList[mid_index+1:]])\n", - "# Use the remaining elements for MGridPrior\n", - "MGridPrior = np.transpose(np.array(mList_without_middle).reshape((Ne, NGrid)))\n" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "#plot the MReference\n", - "fig, ax = plt.subplots(nrows=1, ncols=1) # You can adjust the number of rows and columns as needed\n", - "\n", - "PlotModelRealization(MReference, 'Reference', ax, vmin=bound_min, vmax=bound_max)\n", - "fig.colorbar(im, ax=ax, label='Log of Permeability (mD)')\n", - "ax.set_xlabel('X-axis')\n", - "ax.set_ylabel('Y-axis')\n", - "ax.set_xticks([])\n", - "ax.set_yticks([])\n", - "\n", - "plt.show()\n", - "\n", - "# Create a figure and axis with a specific size\n", - "fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(12, 6))\n", - "\n", - "# Plot your data (assuming PlotModelRealization is a custom function you have)\n", - "im = PlotModelRealization(MGridPrior[:,0], 'Realization 0', ax[0], vmin=bound_min, vmax=bound_max)\n", - "PlotModelRealization(MGridPrior[:,1], 'Realization 1', ax[1], vmin=bound_min, vmax=bound_max)\n", - "# Add colorbar\n", - "fig.colorbar(im, ax=ax, label='Log of Permeability (mD)')\n", - "# Add x and y labels\n", - "for axis in ax:\n", - " axis.set_xlabel('X-axis')\n", - " axis.set_ylabel('Y-axis')\n", - " axis.set_xticks([])\n", - " axis.set_yticks([])\n", - "# Show the plot\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Run the prior models and the reference case" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [], - "source": [ - "#simulate all 101 fields\n", - "simulated_pressure_history = np.zeros((Ne, pressure_history.shape[0], nx, ny))\n", - "for i, perm_field in enumerate(MGridPrior.T):\n", - " reservoir = ReservoirSim(nx, ny, perm_field=np.exp(perm_field))\n", - " pressure_history = reservoir.simulate()\n", - " simulated_pressure_history[i,...] = pressure_history.reshape((pressure_history.shape[0], nx,ny))\n", - "\n", - "simulated_pressure_history_prior = simulated_pressure_history\n", - "#getting only data we will use as observation\n", - "DPrior = simulated_pressure_history[:,:,1,1]" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [], - "source": [ - "#simulate the reference field\n", - "reservoir = ReservoirSim(nx, ny, perm_field=np.exp(MReference))\n", - "pressure_history = reservoir.simulate()\n", - "reference_pressure_history = pressure_history.reshape((pressure_history.shape[0], nx,ny))\n" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[]" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "#plot the monitored pressure at cell (1,1) for all 11 fields - consider the last simulation 101 as the reference case\n", - "for i in range(Ne):\n", - " plt.plot(simulated_pressure_history[i,:,1,1], color='gray', alpha=0.5)\n", - "plt.plot(reference_pressure_history[:,1,1], label='reference case' , marker='o', linestyle='', color = 'red')\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Create the perturbed observations for ESMDA" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We will create a set of perturbed observations that will serve as our observations for ESMDA. These observations are generated by adding a random noise to the reference case observations." - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [], - "source": [ - "#using the last model to create synthetic data\n", - "# Observations\n", - "dObs = reference_pressure_history[:,1,1].flatten()\n", - "Nd = len(dObs)\n", - "dstd = 2 * np.ones_like(dObs)\n", - "# Associated standard deviation: ones (for this scenario)\n", - "dstd = np.ones(dObs.size)*0.1\n", - "Ce = np.diag(dstd**2)\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### ESMDA" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Here we implement the ESMDA algorithm. This involves multiple assimilation steps, where we update our model parameters using observed data. The key components include:\n", - "\n", - "Perturbing the observed data.\n", - "\n", - "Calculating the Kalman gain.\n", - "\n", - "Updating the model parameters.\n", - "\n", - "Each assimilation step refines our model parameters, aiming to reduce the discrepancy between the model and the observed data." - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [], - "source": [ - "Na = 4 #number of assimilation steps\n", - "alphas = np.ones(Na)*Na\n", - "D=np.zeros((Nd,Ne))\n", - "MGrid=np.zeros((NGrid,Ne))" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Assimilation step 0\n", - "\n", - "Assimilation step 1\n", - "\n", - "Assimilation step 2\n", - "\n", - "Assimilation step 3\n" - ] - } - ], - "source": [ - "l=0\n", - "D_iterations=[]\n", - "for alpha_idx, alpha in enumerate(alphas):\n", - " print(f\"\\nAssimilation step {l}\") \n", - " Dobs = np.transpose(dObs + alphas[0]*dstd*np.random.randn(Ne,Nd)) #perturb the observation for each ensemble member\n", - " \n", - " if l==0: \n", - " MGrid = MGridPrior\n", - " D = DPrior \n", - " \n", - " else:\n", - " \n", - " total_simulations = Ne\n", - " \n", - " simulated_pressure_history = np.zeros((Ne, pressure_history.shape[0], nx, ny))\n", - " for i, perm_field in enumerate(MGrid.T):\n", - " reservoir = ReservoirSim(nx, ny, perm_field=np.exp(perm_field))\n", - " pressure_history = reservoir.simulate()\n", - " simulated_pressure_history[i,...] = pressure_history.reshape((pressure_history.shape[0], nx,ny))\n", - " #getting only data we will use as observation\n", - " D = simulated_pressure_history[:,:,1,1] \n", - " \n", - "\n", - " D_iterations.append(D)\n", - "\n", - " \n", - " \n", - " deltaM = np.transpose(MGrid.T-MGrid.mean(axis=1)) #mean of the ensemble parameters\n", - " deltaD = D.T-D.mean(axis=1) #mean of the ensemble data\n", - " K = (deltaM@deltaD.T)@np.linalg.inv((deltaD@deltaD.T + alphas[0]*(Ne-1)*Ce)) #Kalman gain\n", - " Mnew = MGrid + K@(Dobs-D.T) #update the ensemble parameters\n", - " MGrid= np.clip(Mnew, bound_min, bound_max) #clip the ensemble parameters to min = 0.5 and max = 5 (related to MGrid values) \n", - " \n", - " \n", - " \n", - " l += 1\n", - "MGridPost = MGrid\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Posterior Analysis\n", - "After running ESMDA, it's crucial to analyze the posterior ensemble of models. Here, we visualize the first three realizations from both the prior and posterior ensembles to see how the models have been updated." - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(10,5))\n", - "ax[0].imshow(MGridPrior.mean(axis=1).reshape(nx,ny), label = 'Prior Mean')\n", - "ax[0].set_title('Prior Mean')\n", - "ax[1].imshow(MGridPost.mean(axis=1).reshape(nx,ny), label= 'Post Mean')\n", - "ax[1].set_title('Post Mean')\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [], - "source": [ - "#Run the posterior\n", - "simulated_pressure_history = np.zeros((Ne, pressure_history.shape[0], nx, ny))\n", - "for i, perm_field in enumerate(MGridPost.T):\n", - " reservoir = ReservoirSim(nx, ny, perm_field=np.exp(perm_field))\n", - " pressure_history = reservoir.simulate()\n", - " simulated_pressure_history[i,...] = pressure_history.reshape((pressure_history.shape[0], nx,ny))\n", - "DPost = simulated_pressure_history[:,:,1,1]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Observing the monitored pressure at cell (1,1) for all realizations and the reference case, we can see that the ensemble of models after the assimilation steps (in blue) is closer to the reference case (in red) than the prior ensemble (in gray). This indicates that the ESMDA method is effectively updating the models to better represent the observed data." - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[]" - ] - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "#plot the monitored pressure at cell (1,1) for all 11 fields - consider the last simulation 101 as the reference case\n", - "noisy_obs = dObs + np.random.normal(0, dstd , size=len(dObs))\n", - "\n", - "for i in range(Ne):\n", - " plt.plot(DPrior[i,:], color='gray', alpha=0.5)\n", - " plt.plot(DPost[i,:], color='blue', alpha=0.5)\n", - "plt.plot(noisy_obs, label='reference case' , marker='o', linestyle='', color = 'red')" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.8" - }, - "orig_nbformat": 4 - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/reservoir_simulator.py b/notebooks/reservoir_simulator.py deleted file mode 100644 index bade1c9..0000000 --- a/notebooks/reservoir_simulator.py +++ /dev/null @@ -1,158 +0,0 @@ -#%% -import numpy as np -import matplotlib.pyplot as plt - -def progress_bar(iteration, total, bar_length=50): - percent = float(iteration) / float(total) - arrow = '=' * int(round(percent * bar_length) - 1) - spaces = ' ' * (bar_length - len(arrow)) - - sys.stdout.write(f'\r[{arrow + spaces}] {percent * 100:.2f}%') - sys.stdout.flush() - -class ReservoirSim: - def __init__(self, nx, ny, perm_field=None): - # Initialize simulation parameters - self.nx = nx - self.ny = ny - self.nb = nx * ny - self.perm_field = perm_field if perm_field is not None else np.ones(self.nb) * 1000 - - self.phi = 0.2 - self.c_f = 1e-5 - self.p0 = 1 - self.rho0 = 1 - self.mu_w = 1 - self.rw = 0.15 - self.dx = 50 - self.dy = 50 - self.dz = 10 - self.V = self.dx * self.dy * self.dz - - self.pres_ini = 150 - self.pres_prd = 120 - self.pres_inj = 180 - - def compute_beta(self, dens): - Phi = dens / self.mu_w - return Phi - - def compute_wi(self, k, mu, dens): - r0 = 0.208 * self.dx - wi = 2 * np.pi * k * self.dz / mu / np.log(r0 / self.rw) - return wi - - def compute_density(self, p): - dens = self.rho0 * (1 + self.c_f * (p - self.p0)) - return dens - def get_matrix(self, n, Phi, compr, p): - nconn = (self.nx - 1) * self.ny + self.nx * (self.ny - 1) - block_m = np.zeros(nconn, dtype=np.int32) - block_p = np.zeros(nconn, dtype=np.int32) - Trans = np.ones(nconn) - A = self.dx * self.dy - - perm_1d = self.perm_field.flatten() - - for i in range(self.nx - 1): - for j in range(self.ny): - k = i + j * (self.nx - 1) - block_m[k] = i + j * self.nx - block_p[k] = block_m[k] + 1 - gl = perm_1d[block_m[k]] * A / self.dx - gr = perm_1d[block_p[k]] * A / self.dx - Trans[k] = gl * gr / (gl + gr) - - for i in range(self.nx): - for j in range(self.ny - 1): - k = (self.nx-1) * self.ny + i + j * self.nx - block_m[k] = i + j * self.nx - block_p[k] = block_m[k] + self.nx - gl = perm_1d[block_m[k]] * A / self.dy - gr = perm_1d[block_p[k]] * A / self.dy - Trans[k] = gl * gr / (gl + gr) - - - K = np.zeros((n,n)) - f = np.ones(n) * compr * p - for i in range(n): - K[i, i] = compr[i] - - for k in range(nconn): - im = block_m[k] - ip = block_p[k] - K[im, im] += Trans[k] * (Phi[im] + Phi[ip]) / 2 - K[im, ip] -= Trans[k] * (Phi[im] + Phi[ip]) / 2 - K[ip, im] -= Trans[k] * (Phi[im] + Phi[ip]) / 2 - K[ip, ip] += Trans[k] * (Phi[im] + Phi[ip]) / 2 - - return K, f - - def simulate(self): - P = np.ones(self.nb) * self.pres_ini - dt = 0.0001 - pressure_history = [] - for t in range(10): - dens = self.compute_density(P) - beta = self.compute_beta(dens) - wi = self.compute_wi(self.perm_field, self.mu_w, dens) - compr = np.ones(self.nb) * self.V * self.phi * self.c_f / dt - - K, f = self.get_matrix(self.nb, beta, compr, P) - - f[0] += self.pres_inj * wi[0] - K[0, 0] += wi[0] - - f[-1] += self.pres_prd * wi[-1] - K[-1, -1] += wi[-1] - - P = np.linalg.solve(K, f) - pressure_history.append(P.copy()) - - z = np.reshape(P, [self.ny, self.nx]) - - #Visualization - # plt.imshow(z) - # plt.colorbar() - # plt.show() - return np.array(pressure_history) - - # def plot_pressure_grid(self, pressure_history, steps_per_row=3): - # num_steps = len(pressure_history) - # num_rows = (num_steps + steps_per_row - 1) // steps_per_row - - # # Find global minimum and maximum pressure for color scaling - # global_min = np.min([np.min(p) for p in pressure_history]) - # global_max = np.max([np.max(p) for p in pressure_history]) - - # fig, axes = plt.subplots(num_rows, steps_per_row, figsize=(15, num_rows*5)) - - # # Flatten the axes array for easier indexing - # axes = axes.flatten() - - # for i in range(num_steps): - # ax = axes[i] - # z = np.reshape(pressure_history[i], [self.ny, self.nx]) - # im = ax.imshow(z, cmap='viridis', vmin=global_min, vmax=global_max) # Fixed color limits - # ax.set_title(f"Time step {i+1}") - - # # Hide any remaining empty subplots - # for i in range(num_steps, num_rows * steps_per_row): - # axes[i].axis('off') - - # # Adjust layout to make room for colorbar - # plt.subplots_adjust(right=0.8) - - # # Add a colorbar to the figure at the right side - # cbar_ax = fig.add_axes([0.85, 0.15, 0.05, 0.7]) - # fig.colorbar(im, cax=cbar_ax) - - # plt.show() - - - - -# perm_field = np.ones(25 * 25) * 1000 # Replace with your actual perm field -# reservoir = ReservoirSim(perm_field=perm_field) -# pressure_history = reservoir.simulate() -# reservoir.plot_middle_pressure(pressure_history) \ No newline at end of file diff --git a/reports/figures/.gitkeep b/reports/figures/.gitkeep deleted file mode 100644 index e69de29..0000000 diff --git a/requirements-dev.txt b/requirements-dev.txt new file mode 100644 index 0000000..230467f --- /dev/null +++ b/requirements-dev.txt @@ -0,0 +1,24 @@ +# GLOBAL REQUIREMENTS +-r requirements.txt + +# SOFT DEPENDENCIES +matplotlib + +# SETUP RELATED +setuptools_scm + +# FOR DOCUMENTATION +sphinx +numpydoc +sphinx_design +sphinx_numfig +sphinx_gallery +pydata_sphinx_theme +sphinx_automodapi +ipykernel + +# FOR TESTING +flake8 +pytest +coveralls +pytest_cov diff --git a/requirements.txt b/requirements.txt new file mode 100644 index 0000000..9c558e3 --- /dev/null +++ b/requirements.txt @@ -0,0 +1 @@ +. diff --git a/resmda/__init__.py b/resmda/__init__.py new file mode 100644 index 0000000..a7f2bb0 --- /dev/null +++ b/resmda/__init__.py @@ -0,0 +1,26 @@ +# Copyright 2024 Dieter Werthmüller, Gabriel Serrao Seabra +# +# This file is part of resmda. +# +# Licensed under the Apache License, Version 2.0 (the "License"); you may not +# use this file except in compliance with the License. You may obtain a copy +# of the License at +# +# https://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT +# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the +# License for the specific language governing permissions and limitations under +# the License. + +from resmda import utils +from resmda.utils import Report +from resmda.data_assimilation import esmda +from resmda.reservoir_simulator import Simulator, RandomPermeability + + +__all__ = ['reservoir_simulator', 'data_assimilation', 'utils', + 'Simulator', 'RandomPermeability', 'esmda', 'Report'] + +__version__ = utils.__version__ diff --git a/resmda/data_assimilation.py b/resmda/data_assimilation.py new file mode 100644 index 0000000..e50dd80 --- /dev/null +++ b/resmda/data_assimilation.py @@ -0,0 +1,133 @@ +# Copyright 2024 Dieter Werthmüller, Gabriel Serrao Seabra +# +# This file is part of resmda. +# +# Licensed under the Apache License, Version 2.0 (the "License"); you may not +# use this file except in compliance with the License. You may obtain a copy +# of the License at +# +# https://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT +# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the +# License for the specific language governing permissions and limitations under +# the License. + +import numpy as np + +from resmda.utils import rng + +__all__ = ['esmda'] + + +def __dir__(): + return __all__ + + +def esmda(model_prior, forward, data_obs, sigma, alphas=4, data_prior=None, + callback_post=None, return_post_data=False, random=None): + """ESMDA algorithm (Emerick and Reynolds, 2013). + + + Parameters + ---------- + + model_post : ndarray + Prior models of dimension ``(ne, ...)``, where ``ne`` is the number of + ensembles. + + forward : callable + Forward model that takes an ndarray of the shape of the prior models + ``(ne, ...)``, and returns a ndarray of the shape of the prior data + ``(ne, nd)``; ``ne`` is the number of ensembles, ``nd`` the number of + data. + + data_obs : ndarray + Observed data of shape ``(nd)``. + + sigma : float, ndarray + + alphas : {int, ndarray}, default: 4 + es-mda inflation factor + + data_prior : ndarray, default: None + (ne, nd) + + vmin, vmax : float, default: None + + return_data_post : bool, default: False + + + Returns + ------- + + + """ + # Get number of ensembles and time steps + ne = model_prior.shape[0] + nd = data_obs.size + + # Expand sigma if float + if np.asarray(sigma).size == 1: + sigma = np.zeros(nd) + sigma + + # Get alphas + if isinstance(alphas, int): + alphas = np.zeros(alphas) + alphas + else: + alphas = np.asarray(alphas) + + # Copy prior as start of post (output) + model_post = model_prior.copy() + + # Loop over alphas + for i, alpha in enumerate(alphas): + print(f"ESMDA step {i+1}; α={alpha}") + + # == Step (a) of Emerick & Reynolds, 2013 == + # Run the ensemble from time zero. + + # Get data + if i > 0 or data_prior is None: + data_prior = forward(model_post) + + # == Step (b) of Emerick & Reynolds, 2013 == + # For each ensemble member, perturb the observation vector using + # d_uc = d_obs + sqrt(α_i) * C_D^0.5 z_d; z_d ~ N(0, I_N_d) + + zd = rng(random).normal(size=(ne, nd)) + data_pert = data_obs + np.sqrt(alpha) * sigma * zd + + # == Step (c) of Emerick & Reynolds, 2013 == + # Update the ensemble using Eq. (3) with C_D replaced by α_i * C_D + + # Compute the (co-)variances + # Note: The factor (ne-1) is part of the covariances CMD and CDD, + # wikipedia.org/wiki/Covariance#Calculating_the_sample_covariance + # but factored out of CMD(CDD+αCD)^-1 to be in αCD. + cmodel = model_post - model_post.mean(axis=0) + cdata = data_prior - data_prior.mean(axis=0) + CMD = np.moveaxis(cmodel, 0, -1) @ cdata + CDD = cdata.T @ cdata + CD = np.diag(alpha * (ne - 1) * sigma**2) + + # Compute inverse of C + # C is a real-symmetric positive-definite matrix. + # If issues arise in real-world problems, try using + # - a subspace inversions with Woodbury matrix identity, or + # - Moore-Penrose via np.linalg.pinv, sp.linalg.pinv, spp.linalg.pinvh. + Cinv = np.linalg.inv(CDD + CD) + + # Calculate the Kalman gain + K = CMD@Cinv + + # Update the ensemble parameters + model_post += np.moveaxis(K @ (data_pert - data_prior).T, -1, 0) + + # Apply model parameter bounds. + if callback_post: + callback_post(model_post) + + # Return posterior model and corresponding data + return model_post, forward(model_post) diff --git a/resmda/reservoir_simulator.py b/resmda/reservoir_simulator.py new file mode 100644 index 0000000..68ca29e --- /dev/null +++ b/resmda/reservoir_simulator.py @@ -0,0 +1,277 @@ +# Copyright 2024 Dieter Werthmüller, Gabriel Serrao Seabra +# +# This file is part of resmda. +# +# Licensed under the Apache License, Version 2.0 (the "License"); you may not +# use this file except in compliance with the License. You may obtain a copy +# of the License at +# +# https://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT +# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the +# License for the specific language governing permissions and limitations under +# the License. + +import numpy as np +import scipy as sp + +from resmda.utils import rng + +__all__ = ['Simulator', 'RandomPermeability', 'covariance'] + + +def __dir__(): + return __all__ + + +class Simulator: + """A small Reservoir Simulator. + + + """ + + def __init__(self, nx, ny, phi=0.2, c_f=1e-5, p0=1, rho0=1, mu_w=1, + rw=0.15, pres_ini=150, wells=None, dx=50, dz=10): + """Initialize a Simulation instance. + + Parameters + ---------- + nx, ny : int + Dimension of field + phi : float + Porosity (-) + c_f : float + Formation compressibility (1/kPa) + p0 : float + Initial pressure (bar or kPa?) + rho0 : float + Fixed density (kg/m3) + mu_w : float + Viscosity (cP - Pa s) + rw : float + Well radius (m) + pres_ini : initial pressure [?] + wells : location and pressure of wells [?] + dx, dz : floats + Cell dimensions in horizontal (dx) and vertical (dz) + directions (m). + + """ + + self.size = nx*ny + self.shape = (nx, ny) + self.nx = nx + self.ny = ny + + self.phi = phi + self.c_f = c_f + self.p0 = p0 + self.rho0 = rho0 + self.mu_w = mu_w + self.rw = rw + self.dx = dx + self.dz = dz + self.pres_ini = pres_ini + + # Store volumes (needs adjustment for arbitrary cell volumes) + self.volumes = np.ones(self.size) * self.dx * self.dx * self.dz + self._vol_phi_cf = self.volumes * self.phi * self.c_f + + if wells is None: + self.wells = np.array([[0, 0, 180], [self.nx-1, self.ny-1, 120]]) + else: + self.wells = np.array(wells) + + # Get well locations and set terms + self.locs = self.wells[:, 1]*self.nx + self.wells[:, 0] + + @property + def _set_well_terms(self): + # Get well terms + wi = 2 * np.pi * self.perm_field[self.locs] * self.dz + wi /= self.mu_w * np.log(0.208 * self.dx / self.rw) + + # Add wells + self._add_wells_f = self.wells[:, 2] * wi + self._add_wells_d = wi + + def solve(self, pressure, dt): + """Construct K-matrix.""" + + # Mobility ratio without permeability + phi = self.rho0 * (1 + self.c_f * (pressure - self.p0)) / self.mu_w + + # Compr. and right-hand side f + compr = self._vol_phi_cf / dt + f = compr * pressure + + # Pre-allocate diagonals. + mn = np.zeros(self.size) + m1 = np.zeros(self.size) + d = compr + p1 = np.zeros(self.size) + pn = np.zeros(self.size) + + t1 = self.dx * self.perm_field[:-1] * self.perm_field[1:] + t1 /= self.perm_field[:-1] + self.perm_field[1:] + t1 *= (phi[:-1] + phi[1:]) / 2 + t1[self.nx-1::self.nx] = 0.0 + d[:-1] += t1 + d[1:] += t1 + m1[:-1] -= t1 + p1[1:] -= t1 + + t2 = self.dx * self.perm_field[:-self.nx] * self.perm_field[self.nx:] + t2 /= self.perm_field[:-self.nx] + self.perm_field[self.nx:] + t2 *= (phi[:-self.nx] + phi[self.nx:]) / 2 + d[:-self.nx] += t2 + d[self.nx:] += t2 + mn[:-self.nx] -= t2 + pn[self.nx:] -= t2 + + # Add wells. + f[self.locs] += self._add_wells_f + d[self.locs] += self._add_wells_d + + # Bring to sparse matrix + offsets = np.array([-self.nx, -1, 0, 1, self.nx]) + data = np.array([mn, m1, d, p1, pn]) + K = sp.sparse.dia_array((data, offsets), shape=(self.size, self.size)) + + # Solve the system + return sp.sparse.linalg.spsolve(K.tocsc(), f, use_umfpack=False) + + def __call__(self, perm_fields, dt=np.ones(10)*0.0001, data=False): + """Run simulator. + + Parameters + ---------- + dt : array + Time steps. + + """ + if perm_fields.ndim == 2: + ne = 1 + perm_fields = [perm_fields, ] + else: + ne = perm_fields.shape[0] + nt = dt.size+1 + + out = np.zeros((ne, nt, self.nx, self.ny)) + for n, perm_field in enumerate(perm_fields): + + self.perm_field = perm_field.ravel('F') + self._set_well_terms + + pressure = np.ones((dt.size+1, self.size)) * self.pres_ini + for i, d in enumerate(dt): + pressure[i+1, :] = self.solve(pressure[i, :], d) + out[n, ...] = pressure.reshape((dt.size+1, *self.shape), order='F') + if ne == 1: + out = out[0, ...] + + if data: + return out[..., data[0], data[1]] + else: + return out + + +class RandomPermeability: + + def __init__(self, nx, ny, perm_mean, perm_min, perm_max, length=(10, 10), + theta=45, sigma_pr2=1.0, dtype='float32'): + self.nx = nx + self.ny = ny + self.nc = nx*ny + self.perm_mean = perm_mean + self.perm_min = perm_min + self.perm_max = perm_max + self.length = length + self.theta = theta + self.sigma_pr2 = sigma_pr2 + self.dtype = dtype + + @property + def cov(self): + if not hasattr(self, '_cov'): + self._cov = covariance( + nx=self.nx, ny=self.ny, length=self.length, + theta=self.theta, sigma_pr2=self.sigma_pr2, dtype=self.dtype + ) + return self._cov + + @property + def lcho(self): + if not hasattr(self, '_lcho'): + self._lcho = sp.linalg.cholesky(self.cov, lower=True) + return self._lcho + + def __call__(self, n, perm_mean=None, perm_min=None, perm_max=None, + random=None): + if perm_mean is None: + perm_mean = self.perm_mean + if perm_min is None: + perm_min = self.perm_min + if perm_max is None: + perm_max = self.perm_max + out = np.full((n, self.nx, self.ny), perm_mean, order='F') + for i in range(n): + z = rng(random).normal(size=self.nc) + out[i, ...] += (self.lcho @ z).reshape( + (self.nx, self.ny), order='F') + + return out.clip(perm_min, perm_max) + + +def covariance(nx, ny, length, theta, sigma_pr2, dtype='float32'): + """Build co-variance matrix for permeability. + + Parameters + ---------- + nx, ny : int + Number of cells in x and y + theta : float + Angle (in degrees) + """ + nc = nx*ny + cost = np.cos(theta) + sint = np.sin(theta) + + # 1. Fill the first row nx * nc, but vertically + tmp1 = np.zeros([nx, nc], dtype=dtype) + for i in range(nx): + tmp1[i, 0] = 1.0 # diagonal + for j in range(i+1, nc): + d0 = (j % nx) - i + d1 = (j // nx) + rot0 = cost*d0 - sint*d1 + rot1 = sint*d0 + cost*d1 + hl = np.sqrt((rot0/length[0])**2 + (rot1/length[1])**2) + + # Calculate value. + if sigma_pr2: # Sphere formula + if hl <= 1: + tmp1[i, j-i] = sigma_pr2 * (1 - 1.5*hl + hl**3/2) + + else: # Gaspari Cohn + if hl < 1: + tmp1[i, j-i] = (-(hl**5)/4 + (hl**4)/2 + (hl**3)*5/8 - + (hl**2)*5/3 + 1) + elif hl >= 1 and hl < 2: + tmp1[i, j-i] = ((hl**5)/12 - (hl**4)/2 + (hl**3)*5/8 + + (hl**2)*5/3 - hl*5 + 4 - (1/hl)*2/3) + + # 2. Get the indices of the non-zero columns + ind = np.where(tmp1.sum(axis=0))[0] + + # 3. Expand the non-zero colums ny-times + tmp2 = np.zeros([nc, ind.size], dtype=dtype) + for i, j in enumerate(ind): + n = j//nx + tmp2[:nc-n*nx, i] = np.tile(tmp1[:, j], ny-n) + + # 4. Construct array through sparse diagonal array + cov = sp.sparse.dia_array((tmp2.T, -ind), shape=(nc, nc)) + return cov.toarray() diff --git a/resmda/utils.py b/resmda/utils.py new file mode 100644 index 0000000..19bdae5 --- /dev/null +++ b/resmda/utils.py @@ -0,0 +1,78 @@ +# Copyright 2024 Dieter Werthmüller, Gabriel Serrao Seabra +# +# This file is part of resmda. +# +# Licensed under the Apache License, Version 2.0 (the "License"); you may not +# use this file except in compliance with the License. You may obtain a copy +# of the License at +# +# https://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT +# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the +# License for the specific language governing permissions and limitations under +# the License. + +from datetime import datetime + +import numpy as np +from scooby import Report as ScoobyReport + +try: + from resmda.version import version as __version__ +except ImportError: + __version__ = 'unknown-'+datetime.today().strftime('%Y%m%d') + + +__all__ = ['Report', 'rng'] + + +def __dir__(): + return __all__ + + +# Instantiate a random number generator ONCE +RANDOM_NUMBER_GENERATOR = np.random.default_rng() + + +def rng(random=None): + """Module-wide Random Number Generator. + + Mainly meant for internal use. + + + Parameters + ---------- + random : {None, int, np.random.Generator}, default: None + - If ``None`` it returns a :func:`numpy.random.default_rng()` instance + instantiated on a module level. + - If ``int``, it returns a newly created + :func:`numpy.random.default_rng()`` instance, instantiated with + ``int`` as seed. + - If it is already a :class:`numpy.random.Generator` instance, it + simply returns it. + + + Returns + rng : random number generator + A :class:`numpy.random.Generator` instance. + + """ + if isinstance(random, int): + return np.random.default_rng(random) + elif isinstance(random, np.random.Generator): + return random + else: + return RANDOM_NUMBER_GENERATOR + + +class Report(ScoobyReport): + """Print a Scooby report; see ``scooby.Report()`` for info.""" + + def __init__(self, **kwargs): + """Initiate a scooby.Report instance.""" + kwargs = {'ncol': 3, **kwargs} + kwargs['core'] = ['numpy', 'scipy', 'numba', 'resmda'] + kwargs['optional'] = ['matplotlib', 'IPython'] + super().__init__(**kwargs) diff --git a/setup.cfg b/setup.cfg new file mode 100644 index 0000000..9630c6c --- /dev/null +++ b/setup.cfg @@ -0,0 +1,2 @@ +[flake8] +per-file-ignores = __init__.py: F401 diff --git a/setup.py b/setup.py new file mode 100644 index 0000000..f25e3a9 --- /dev/null +++ b/setup.py @@ -0,0 +1,34 @@ +# -*- coding: utf-8 -*- +import os +from setuptools import setup + +# Get README +with open("README.rst") as f: + readme = f.read() + +setup( + name="resmda", + description="A simple 2D reservoir modeller plus ESMDA.", + long_description=readme, + author="Dieter Werthmüller, Gabriel Serrao Seabra", + author_email="info@emsig.xyz", + url="https://github.com/tuda-geo/resmda", + license="Apache-2.0", + packages=["resmda"], + classifiers=[ + "Development Status :: 3 - Alpha", + "License :: OSI Approved :: Apache Software License", + "Programming Language :: Python", + ], + python_requires=">=3.10", + install_requires=[ + "scipy", + "scooby", + ], + use_scm_version={ + "root": ".", + "relative_to": __file__, + "write_to": os.path.join("resmda", "version.py"), + }, + setup_requires=["setuptools_scm"], +) diff --git a/src/data/.gitkeep b/src/data/.gitkeep deleted file mode 100644 index e69de29..0000000 diff --git a/src/models/reservoir_simulator.py b/src/models/reservoir_simulator.py deleted file mode 100644 index bade1c9..0000000 --- a/src/models/reservoir_simulator.py +++ /dev/null @@ -1,158 +0,0 @@ -#%% -import numpy as np -import matplotlib.pyplot as plt - -def progress_bar(iteration, total, bar_length=50): - percent = float(iteration) / float(total) - arrow = '=' * int(round(percent * bar_length) - 1) - spaces = ' ' * (bar_length - len(arrow)) - - sys.stdout.write(f'\r[{arrow + spaces}] {percent * 100:.2f}%') - sys.stdout.flush() - -class ReservoirSim: - def __init__(self, nx, ny, perm_field=None): - # Initialize simulation parameters - self.nx = nx - self.ny = ny - self.nb = nx * ny - self.perm_field = perm_field if perm_field is not None else np.ones(self.nb) * 1000 - - self.phi = 0.2 - self.c_f = 1e-5 - self.p0 = 1 - self.rho0 = 1 - self.mu_w = 1 - self.rw = 0.15 - self.dx = 50 - self.dy = 50 - self.dz = 10 - self.V = self.dx * self.dy * self.dz - - self.pres_ini = 150 - self.pres_prd = 120 - self.pres_inj = 180 - - def compute_beta(self, dens): - Phi = dens / self.mu_w - return Phi - - def compute_wi(self, k, mu, dens): - r0 = 0.208 * self.dx - wi = 2 * np.pi * k * self.dz / mu / np.log(r0 / self.rw) - return wi - - def compute_density(self, p): - dens = self.rho0 * (1 + self.c_f * (p - self.p0)) - return dens - def get_matrix(self, n, Phi, compr, p): - nconn = (self.nx - 1) * self.ny + self.nx * (self.ny - 1) - block_m = np.zeros(nconn, dtype=np.int32) - block_p = np.zeros(nconn, dtype=np.int32) - Trans = np.ones(nconn) - A = self.dx * self.dy - - perm_1d = self.perm_field.flatten() - - for i in range(self.nx - 1): - for j in range(self.ny): - k = i + j * (self.nx - 1) - block_m[k] = i + j * self.nx - block_p[k] = block_m[k] + 1 - gl = perm_1d[block_m[k]] * A / self.dx - gr = perm_1d[block_p[k]] * A / self.dx - Trans[k] = gl * gr / (gl + gr) - - for i in range(self.nx): - for j in range(self.ny - 1): - k = (self.nx-1) * self.ny + i + j * self.nx - block_m[k] = i + j * self.nx - block_p[k] = block_m[k] + self.nx - gl = perm_1d[block_m[k]] * A / self.dy - gr = perm_1d[block_p[k]] * A / self.dy - Trans[k] = gl * gr / (gl + gr) - - - K = np.zeros((n,n)) - f = np.ones(n) * compr * p - for i in range(n): - K[i, i] = compr[i] - - for k in range(nconn): - im = block_m[k] - ip = block_p[k] - K[im, im] += Trans[k] * (Phi[im] + Phi[ip]) / 2 - K[im, ip] -= Trans[k] * (Phi[im] + Phi[ip]) / 2 - K[ip, im] -= Trans[k] * (Phi[im] + Phi[ip]) / 2 - K[ip, ip] += Trans[k] * (Phi[im] + Phi[ip]) / 2 - - return K, f - - def simulate(self): - P = np.ones(self.nb) * self.pres_ini - dt = 0.0001 - pressure_history = [] - for t in range(10): - dens = self.compute_density(P) - beta = self.compute_beta(dens) - wi = self.compute_wi(self.perm_field, self.mu_w, dens) - compr = np.ones(self.nb) * self.V * self.phi * self.c_f / dt - - K, f = self.get_matrix(self.nb, beta, compr, P) - - f[0] += self.pres_inj * wi[0] - K[0, 0] += wi[0] - - f[-1] += self.pres_prd * wi[-1] - K[-1, -1] += wi[-1] - - P = np.linalg.solve(K, f) - pressure_history.append(P.copy()) - - z = np.reshape(P, [self.ny, self.nx]) - - #Visualization - # plt.imshow(z) - # plt.colorbar() - # plt.show() - return np.array(pressure_history) - - # def plot_pressure_grid(self, pressure_history, steps_per_row=3): - # num_steps = len(pressure_history) - # num_rows = (num_steps + steps_per_row - 1) // steps_per_row - - # # Find global minimum and maximum pressure for color scaling - # global_min = np.min([np.min(p) for p in pressure_history]) - # global_max = np.max([np.max(p) for p in pressure_history]) - - # fig, axes = plt.subplots(num_rows, steps_per_row, figsize=(15, num_rows*5)) - - # # Flatten the axes array for easier indexing - # axes = axes.flatten() - - # for i in range(num_steps): - # ax = axes[i] - # z = np.reshape(pressure_history[i], [self.ny, self.nx]) - # im = ax.imshow(z, cmap='viridis', vmin=global_min, vmax=global_max) # Fixed color limits - # ax.set_title(f"Time step {i+1}") - - # # Hide any remaining empty subplots - # for i in range(num_steps, num_rows * steps_per_row): - # axes[i].axis('off') - - # # Adjust layout to make room for colorbar - # plt.subplots_adjust(right=0.8) - - # # Add a colorbar to the figure at the right side - # cbar_ax = fig.add_axes([0.85, 0.15, 0.05, 0.7]) - # fig.colorbar(im, cax=cbar_ax) - - # plt.show() - - - - -# perm_field = np.ones(25 * 25) * 1000 # Replace with your actual perm field -# reservoir = ReservoirSim(perm_field=perm_field) -# pressure_history = reservoir.simulate() -# reservoir.plot_middle_pressure(pressure_history) \ No newline at end of file diff --git a/src/tools/.gitkeep b/src/tools/.gitkeep deleted file mode 100644 index e69de29..0000000 diff --git a/src/visualization/.gitkeep b/src/visualization/.gitkeep deleted file mode 100644 index e69de29..0000000 diff --git a/tests/test_utils.py b/tests/test_utils.py new file mode 100644 index 0000000..dc5c3d0 --- /dev/null +++ b/tests/test_utils.py @@ -0,0 +1,10 @@ +import numpy as np + +from resmda import utils + + +def test_random(): + assert isinstance(utils.rng(), np.random.Generator) + assert isinstance(utils.rng(11), np.random.Generator) + rng = np.random.default_rng() + assert rng == utils.rng(rng)