https://github.com/equinor/si4ti
si4ti is a LGPL licensed seismic inversion tool for monitoring effects in 4D seismic from changes in acoustic properties of a reservoir.
https://github.com/equinor/si4ti
cli impedance python3 seismic seismic-inversion timeshift
Last synced: 11 months ago
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si4ti is a LGPL licensed seismic inversion tool for monitoring effects in 4D seismic from changes in acoustic properties of a reservoir.
- Host: GitHub
- URL: https://github.com/equinor/si4ti
- Owner: equinor
- License: lgpl-2.1
- Created: 2021-05-10T16:12:57.000Z (about 5 years ago)
- Default Branch: main
- Last Pushed: 2025-06-26T11:44:39.000Z (about 1 year ago)
- Last Synced: 2025-07-27T14:50:32.764Z (12 months ago)
- Topics: cli, impedance, python3, seismic, seismic-inversion, timeshift
- Language: C++
- Homepage: https://pypi.org/project/si4ti/
- Size: 18.5 MB
- Stars: 4
- Watchers: 3
- Forks: 5
- Open Issues: 4
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
## Introduction ##
si4ti is a LGPL licensed seismic inversion tool for monitoring effects in 4D
seismic from changes in acoustic properties of a reservoir.
### Timeshift ###
si4ti timeshift computes the dynamic timeshift between traces of different
datasets (vintages). It uses vertical and horizontal smoothing constraints, and
no prior information.
### Impedance ###
si4ti impedance uses a statistical wavelet and lateral, horizontal and 4D
smoothing for computing the relative acoustic impedance of a set of vintages.
## Installation ##
Pre-built executables for Linux can be downloaded from
[here](https://github.com/equinor/si4ti/releases).
## Build from source ##
We provide two build flags that let you turn on and off the timeshift
(`BUILD_TIMESHIFT`) and impedance (`BUILD_IMPEDANCE`) tools. By default, both
tools are built.
To build si4ti you need:
* A C++11 compatible compiler (tested on gcc)
* [CMake](https://cmake.org) version 3.15 or greater
* [Eigen3](https://eigen.tuxfamily.org) version 3.3.4 or greater
* [OpenMP](https://www.openmp.org)
* [segyio](https://github.com/equinor/segyio) run cmake with `EXPERIMENTAL=ON`
to get the required C++ headers
* [fftw](https://www.fftw.org) If built with `USE_FFTW=True`
* [Boost](https://www.boost.org) `math` module version 1.76 or greater if
`BUILD_TIMESHIFT=ON`
To build the documentation you also need:
* [sphinx](https://pypi.org/project/Sphinx)
To build and install si4ti run the following commands in your console:
```bash
git clone https://github.com/equinor/si4ti
mkdir si4ti/build
cd si4ti/build
cmake .. -DCMAKE_BUILD_TYPE=Release
make
make install
```
To build the documentation run:
```bash
cmake .. -DBUILD_DOC=TRUE
make doc
```
## Usage ##
For more information on how to run the programs:
```bash
timeshift --help
impedance --help
apply-timeshift --help
```
## Python bindings ##
si4ti provides a Python bindings for the impedance calculations. No Python
interface for the timeshift is provided.
### Installation ###
Pre-built wheels are available for the following platforms for Python 3.10 up to
3.13:
* `manylinux_2_28` for `x86_64`
* MacOS X 14.0 and newer for `arm64`
* MacOS X 13.0 and newer for `x86_64`
The pre-built wheels can be installed via `pip`
```bash
pip install si4ti
```
si4ti is compute intense and highly profits from compiler optimisation and
vectorisation. Therefore, the prebuilt wheels have vectorisation enabled, but
still aim for good portability. The `x86_64` wheels use `x86-64-v3`
architecture optimisations which should be supported by Intel Haswell (released
2013), AMD Excavator, and newer CPUs, see [the GCC documentation for more
information](https://gcc.gnu.org/onlinedocs/gcc/x86-Options.html) and overview
of [microarchitecture levels on
Wikipedia](https://en.wikipedia.org/wiki/X86-64#Microarchitecture_levels). The
`arm64` wheels are currently using the default optimisation chosen by the
compiler and should be portable between all `arm64` platforms.
### Build from source ###
You can install si4ti from source via the the Git repository. This allows to
compile the package with FFTW3 support as well as platform specific
optimisation which may improve the performance.
During compilation, you need the following dependencies.
* A C++11 compatible compiler (tested on gcc and clang)
* Python 3.10 or greater including the development headers
* [CMake](https://cmake.org) version 3.15 or greater
* [Eigen3](https://eigen.tuxfamily.org) version 3.3.4 or greater
* [OpenMP](https://www.openmp.org)
* [fftw](https://www.fftw.org) if the bindings are built with `USE_FFTW=ON`
Compilation of the Python bindings via `pip` only builds the bindings and not
the command line tools. One can specify compile options directly during the
`pip` invocation similarly to using CMake directly. The following command
builds and installs the Python bindings in test configuration with OpenMP and
FFTW on MacOS from the `python/` directory of the repository.
First change into the `python/` directory
```bash
cd python/
```
and then invoke the build process via pip
```bash
OpenMP_ROOT="/opt/homebrew/opt/libomp" pip install -Ccmake.define.USE_FFTW=ON .[test]
```
Afterwards you can run the tests
```bash
python -m pytest --memray tests
```
Note, that you are expected to observe increased performance if compiling with
platform specific optimisation. You can add relevant compiler flags either via
the `CXXFLAGS` environment variable or the CMake parameter `CMAKE_CXX_FLAGS`
(via `-Ccmake.define.CMAKE_CXX_FLAGS=`).
### Usage ###
The interface is inspired by the command line interface. Please check the
Python help for details. You can find the Python help via
```python
import si4ti
help(si4ti)
```