MATLAB and Simulink let you customize and speed up the testing and evaluation of upstream and downstream processes via dynamic modeling and simulation. These capabilities can optimize asset performance and production with minimum operating costs and maximum returns on investment.
With MATLAB and Simulink, you can:
- Customize and scale up 3D design, modeling, and simulation of subsurface and surface processes in conventional, unconventional, or storage reservoirs
- Analyze seismic and wellbore data in multiple domains using image, signal, and wavelet processing algorithms
- Speed up large-scale data analysis using computer vision (image and signal processing) and data science (AI, machine learning, and deep learning) with high-power computing (HPC) capabilities
- Interconnect MATLAB and Simulink with external software applications, create your own application, and automatically generate code as required
Energy Resources Products Developed in MATLAB and Simulink
With MATLAB and Simulink, you can customize modeling and simulation of conventional, unconventional, carbon capture and storage (CCS), and new energy processes using:
Data Science and HPC Toolsets: Developed in MATLAB, these toolsets provide digital technology solutions with customizable toolboxes in various areas:
- AI: Machine learning, deep learning, reinforcement learning
- HPC: Parallel, GPU, cloud, and quantum computing; production server
- IPCV: Image, signal, and wavelet processing; computer vision; GIS
Upstream Products: MATLAB supports geoscientists and engineers in subsurface and surface process modeling and simulation:
- SeReM: 3D seismic modeling, inversion, and classification of petrophysical subsurface properties (developed by Professor Dario Grana)
- MRST: 3D subsurface modeling, simulation, and automation of compositional fluid dynamics using geologically-conformable grids (developed by SINTEF)
- Digital Twin for Modeling and Automation of Drilling Systems
- MATLAB and Simulink for Predictive Maintenance
- MathWorks Energy Symposium 2023 (8 videos)
Downstream Products: Simulink supports scientists and engineers in production and manufacturing process modeling and simulation:
Resources
Subsurface Modeling and Simulation Applications with MATLAB
Subsurface Modeling with SeReM
Model and classify reservoir facies using rock property modeling and seismic inversion algorithms.
Subsurface Simulation with MRST
Model and simulate complex dynamic reservoirs properties using compositional fluid dynamics.
Oil and Gas Production Optimization in MATLAB
Leverage powerful solvers for tackling nonlinear optimizations problems with MATLAB.
Data Science Applications with MATLAB
Oil and Gas Production Data Analysis with MATLAB
Explore data, build machine learning models, and do predictive analytics.
Big Data with MATLAB
Explore, analyze, and develop predictive models on big data.
Seismic Facies Classification with Deep Learning and Wavelets (54:28)
Watch how applying signal processing techniques before AI algorithms helped win the SEAM AI Applied Geoscience GPU Hackathon.
High-Power Computing Applications with MATLAB
Parallel (CPU and GPU) Computing with MATLAB and Simulink
Perform large-scale computations and parallelize simulations using multicore desktops, GPUs, clusters, and clouds.
Cloud Computing with MATLAB and Simulink
Speed up development processes with on-demand access to enhanced compute resources, software tools, and reliable data storage.
Quantum Computing with MATLAB and Simulink
Build, simulate, and run quantum algorithms with MATLAB Support Package for Quantum Computing.
Image Processing and Computer Vision Applications with MATLAB
Image Processing Toolbox
Perform image processing, visualization, and analysis.
Signal Processing Toolbox
Perform signal processing and analysis.
Wavelet Toolbox
Perform time-frequency and wavelet analysis of signals and images.
Computer Vision Toolbox
Design and test computer vision, 3D vision, and video processing systems.
Facies Classification with Wavelets and Deep Learning (25:29)
Apply deep learning and wavelets in MATLAB as a starting point to speed up interpretation.
Seismic Raster to SEG-Y Converter
Convert seismic images into georeferenced SEG-Y format files.
Examples of AI, High-Power Computing, and Image Processing and Computer Vision Applications
Shell Geologists Develop and Deploy Software for Predicting Subsurface Geologic Features
Shell develops an application for quantitatively characterizing subsurface geologic features to reduce oil and gas exploration costs.
Sinopec Develops High Accuracy Intelligent Seismic Inversion with Deep Learning
Sinopec engineers use MATLAB to introduce a new seismic inversion method called frequency-phase intelligent inversion.
Seismic Dip Guided Horizon Interpretation in Petrel with MATLAB (9:50)
Chevron integrates MATLAB with Petrel to design and implement a seismic dip guided horizon auto-tracking algorithm.
How MATLAB Distributed Computing Server and Machine Vision Tools Are Transforming Shell (19:44)
Shell and the AACoE use MDCS to bring its engineers AI tools to speed up processes while increasing their reliability.
Breaking the Boundaries: Integrating GIS, AI, and Lidar for Digital Innovation (24:09)
Engineers at Spacesium use MATLAB to rapidly segment and classify point cloud data.
MATLAB and Advanced Analytics at Shell (29:14)
Shell builds analytics stacks to serve algorithms for process monitoring and predictive analytics based on a three-step approach.
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