Python seismic

Posted on 18.04.2021 Comments

Released: Feb 8, View statistics for this project via Libraries. Tags seismic, geocomputing, geophysics. Alternative commercial license terms are available from Sixty North AS if you wish to redistribute Segpy as part of a proprietary closed source product or deliver software software-as-a-service SaaS using Segpy as part of a proprietary closed source service. The SEG-Y file format is one of several standards developed by the Society of Exploration Geophysicists for storing geophysical seismic data.

On the last line of the example we write the Dataset out to a different file, this time with standard compliant big-endian byte order.

This means overal memory usage is very low, and the program can handle arbitrarily large SEG-Y files. The easiest way to contribute is to use Segpy submit reports for defects or any other issues you come across. Segpy was created by — and to meet the needs of — Sixty North. Segpy 2. No attempt has been made to maintain API compatibility with earlier versions of Segpy and no code is shared across versions.

Earlier versions of Segpy are deprecated and completely unsupported. Feb 8, Feb 7, May 5, Feb 24, Download the file for your platform. If you're not sure which to choose, learn more about installing packages. Warning Some features may not work without JavaScript. Please try enabling it if you encounter problems. Search PyPI Search. Latest version Released: Feb 8, This is a list of free and open-source software for geophysical data processing and interpretation.

SEISMIC: A Self-Exciting Point Process Model for Predicting Tweet Popularity

The list is split into broad categories, depending on the intended use of the software and its scope of functions. Notice that 'free and open-source' requires that the source code is available. Simple being 'free of charge' is not sufficient—see gratis versus libre. The reader interested in freeware just free of charge software is referred to the list of freeware geophysics software.

These are full-featured reflection seismology processing packages, with support for modeling, imaging, and inversion. They are relatively low-level and in some cases have their own data formats and involve learning an extensive syntax or meta-language. These packages offer some subset of functionality of the full processing packages in the previous section. The following projects are not free and open-source.

They have unknown licensing, licenses which place some restriction on use or redistribution, or depend on non-open-source software like MATLABand thus do not meet the Open Source Definition from the Open Source Initiative. For example, the license may rule out use by certain people or for certain purposes, e. They are included here because they may be of interest for those in an academic environment or access to tools like MATLAB.

Airborne Electromagnetic Inversion Software [82]. From Wikipedia, the free encyclopedia. Redirected from List of free geophysics software. This article has multiple issues. Please help improve it or discuss these issues on the talk page. Learn how and when to remove these template messages.

python seismic

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python seismic

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Please help improve it by replacing them with more appropriate citations to reliable, independent, third-party sources. Retrieved Archived from the original on GitHub is home to over 50 million developers working together to host and review code, manage projects, and build software together. If nothing happens, download GitHub Desktop and try again. If nothing happens, download Xcode and try again. If nothing happens, download the GitHub extension for Visual Studio and try again.

The official documentation is hosted on readthedocs. Segyio is an attempt to create an easy-to-use, embeddable, community-oriented library for seismic applications.

Tutorial for the instalation of Gempy in Anaconda for Windows

Features are added as they are needed; suggestions and contributions of all kinds are very welcome. To catch up on the latest development and features, see the changelog.

To write future proof code, consult the planned breaking changes. When segyio is built and installed, you're ready to start programming! Check out the tutorialexamplesexample programsand example notebooks. For a technical reference with examples and small recipes, read the docs. API docs are also available with pydoc - start your favourite Python interpreter and type help segyiowhich should integrate well with IDLE, pycharm and other Python tools.

To build the documentation, you also need sphinx. It's recommended to build in debug mode to get more warnings and to embed debug symbols in the objects. All tests can be run by invoking ctest. Feel free to use the tests already written as a guide. After building segyio you can run the tests with ctestexecuted from the build directory. Please note that to run the Python examples you need to let your environment know where to find the Python library.

This tutorial assumes you're familiar with Python and numpy. For a refresh, check out the python tutorial and numpy quickstart.In this paper, we share the specific code of Python seismic data visualization for your reference. The specific content is as follows. Problem 2 abnormal encoding of configuration file. Check carefully and find that there are abnormal characters in config.

Correct the wrong characters in config. Question 3 Python debugging print statement. Problem 1 the sampling value of the data channel is abnormal. Problem 2 abnormal volume header of data file. Cygwin executes the instruction, and you can see that the feedback information is color, so it is very convenient to analyze the information.

In contrast, the readability of the feedback information after the CMD terminal executes the instruction is poor.

python seismic

After the local data is abnormal, it can be modified by segyread, sushw, sugain, segywrite and other programs in CWP to meet the requirements of drawing program. The above is the whole content of this article.

I hope it will help you in your study, and I hope you can support developepaer more. After working, I try to build […]. Py", linein from "segy return cls. Tags: Python data visualizationPython seismic dataVisualization of Python seismic data.

Centos7 hands on building deep learning environment from scratch tensorflow 2. Pre: A tutorial for creating a custom Ruby gem package. Next: Using skill of return value of InputBox function in vbs.Lutz Gross. GitHub is home to over 50 million developers working together to host and review code, manage projects, and build software together. If nothing happens, download GitHub Desktop and try again. If nothing happens, download Xcode and try again. If nothing happens, download the GitHub extension for Visual Studio and try again.

D student Zhengguang Zhao seismic data processing topic only. Later on, Dr. Lutz Gross taught this course at Jilin University. As most of examples in the Jupyter Notebook tutorials use Esys-Escript package as its backend, users needs to download and install it correctly on their own computers.

A more convenient way using VirtualBox to learn this course is also provided. Here are the steps to get your programming environment ready. Plese note this. Updates hosted on this Github repository have not been added to the course materials. If you have any questions, please contact the course teaching assistant Zhengguang Zhao. Skip to content. Dismiss Join GitHub today GitHub is home to over 50 million developers working together to host and review code, manage projects, and build software together.

Sign up. Branch: master. Go back. Launching Xcode If nothing happens, download Xcode and try again. Latest commit. Git stats 6 commits 1 branch 0 tags. Failed to load latest commit information. View code. This should be as simple as downloading a bash script called something like "Anaconda Once Anaconda Python has been installed, you can install escript by running: conda install esys-escript -c aellery -c conda-forge Method 2 A more convenient way using VirtualBox to learn this course is also provided.

Download and install VirtualBox host software; Download pythonescriptTutorial. Resources Readme. Releases No releases published. You signed in with another tab or window. Reload to refresh your session. You signed out in another tab or window.Programming is becoming an increasingly useful skill for the modern geoscientist. But programming can and will super-charge your work, making you more productive and more thorough.

We can write code to outline a problem, design tests, collect or compute data, or to execute large, repetitive tasks, freeing us to ask questions. Sound programming practices share the same qualities that we hold in high regard as scientists and technologists: work that is well-documented, reproducible, testable, and verifiable for correctness and accuracy.

One of the factors influencing the pattern of sources and receivers in a seismic survey is the range of useful offsets over the depth interval of interest Cooper, We can model the shape of major reflectors starting with an estimate of a root-mean-squared RMS velocity profile or interval velocity profile from sonic log Figure 1. For shallow targets, this range is limited to near offsets, due to direct waves and first breaks.

For deeper targets, the range is limited at far offsets by energy losses due to geometric spreading, moveout stretch, and system noise. In seismic surveying, one must choose a spacing interval between geophones along a receiver line.

If phones are spaced close together, we can collect plenty of samples in a small area. If the spacing is far apart, the sample density goes down, but we can collect data over a bigger area. So there is a trade-off and we want to maximize both; high sample density covering the largest possible area.

In the CMP domain, the direct arrivals show up as linear events, which are eventually discarded by the so-called top-mute operation before stacking or migration. However, if the reflections arrive later than the air blast noise or ground roll noise — pervasive at near offsets — they get caught up in noise too.

Instead, the gathers are attacked with algorithms to eliminate the noise. The extent of each hyperbola that passes through to migration is what we call the range of useful offsets. The deepest reflections have plenty of useful offsets. However if we wanted to do adequate imaging somewhere between the first two reflections in our model gather, for instance, then we need to make sure that we record redundant ray paths over this smaller range as well.

This is related to the notion of aperture: the shallow reflection is restricted in the number of offsets that it can be illuminated with, the deeper reflections can tolerate a larger aperture. This layout suggests merely 4 or 5 ray paths will hit the uppermost reflector at ms.

The deepest reflections however, should have plenty of fold as long as NMO stretch, geometric spreading, and noise levels are treatable. Not only does it require a velocity profile, which may well be derived from a sonic log, VSP, or stacking velocity picks from a nearby seismic line, but it also requires an estimation of the the speed, intensity, and duration of the near surface events to be muted.

These are parameters that depend largely on the nature of the source and the local ground conditions, which vary from place to place, and from one season to the next. Shot records from nearby surveys may be helpful in refining the slopes of the linear near-surface events, but field tests is the only sure way to get robust measures of the surface and near surface velocities.

There are a number of ways to lay out sources and receivers for a 3D seismic survey. In forested areas, a designer may choose a pattern that minimizes the number of trees that need to be felled. Where land access is easier, designers may opt for a pattern that is efficient for the recording crew to deploy and pick up receivers.

However, no matter what survey pattern is used, most geometries consist of receivers strung together along receiver lines and source points placed along source lines. The pairing of source points with live receiver stations comprises the collection of traces that go into making a seismic volume.

An orthogonal surface pattern, with receiver lines laid out perpendicular to the source lines, is the simplest surface geometry to think about. This pattern can be specified over an area of interest by merely choosing spacing intervals between the lines, plus station intervals along the lines. For instance:. These 8 parameters allow us to construct the source and receiver pattern; the coordinates of each source and receiver location.

We can calculate the number of receiver lines and source lines, as well as the number of receivers and sources for each. To make a map of the ideal surface locations, we simply pass this list of x and y coordinates to a scatter plot, shown in Figure 3.This is part of Python for Geosciences notes. When people say that they do their scientific computations in Python it's only half true. Python is a construction set, similar to MITgcm or other models.

Without packages it's only a core, that although very powerful, does not seems to be able to do much by itself. In order to be productive you need comfortable environment, and this is what IPython provide.

It was started as enhanced python interactive shell, but with time become architecture for interactive computing. There are comments.

Comparison of free geophysics software

Python is a widely used general-purpose, high-level programming language. Its design philosophy emphasizes code readability, and its syntax allows programmers to express concepts in fewer lines of code than would be possible in languages such as C. The language provides constructs intended to enable clear programs on both a small and large scale.

Matplotlib is a python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms. Iris seeks to provide a powerful, easy to use, and community-driven Python library for analysing and visualising meteorological and oceanographic data sets.

Kind of Ferret replacement. Developed in the Met Office by group of 7 full time developers. There are more than active python users in Met Office. Lectures on Scientific Computing with Python. A gallery of interesting IPython Notebooks - constant source of inspiration :. It can be tutorials, descriptions of the modules, small scripts, or just tricks, that you think might be useful for others.

There is a set of packages, that almost every scientist would need:. We are going to talk about all exept Sympy. Python uses duck typing. Let's prepare some data:. Easily produce graphs and maps via integration with matplotlib and cartopy. Here is small collection of links that I find useful.