Big Data Image Analysis

MATLAB for Big Data and Image Analysis in Energy Resources

Accelerate the processing and analysis of large-scale data and images

MATLAB accelerates the processing and analysis of both large-scale and real-time datasets including images and signals. It uses scalable and adaptive tools that integrate AI, high-performance computing, and signal and image processing capabilities. These features maximize data and image consumption and minimize turnaround times.

MATLAB is the integrated software platform for energy scientists and engineers to:

Analyze ultra-large datasets with parallel computing and GPU acceleration
Accelerate machine learning and deep learning to make data-driven decisions in real time
Automate anomaly detection and recognition with image processing and computer vision
Customize and deploy applications on IT infrastructure on-premises, in the cloud, or at the edge of the network

“High-performance computing with MATLAB enables us to process previously unanalyzed big data. We translate what we learn into an understanding of how human activities affect the health of ecosystems to inform responsible decisions about what humans do in the ocean and on land.”
Dr. Christopher Clark, Cornell University

Applications

Big data and image analysis in upstream energy

Streamline subsurface imaging with MATLAB

Accelerate large-scale seismic modeling and migration using full-waveform inversion (FWI) and reverse time migration (RTM) algorithms, enhanced by high-performance computing in MATLAB.

Facies Classification with Wavelets and Deep Learning

Streamline subsurface interpretation with MATLAB

Accelerate and automate seismic facies classification using wavelet signal decomposition. This method informs deep learning neural networks empowered by high-performance computing in MATLAB.

Accelerate subsurface data analysis with MATLAB

Discover how ARKCLS expedites subsurface data analysis by interconnecting digital interpretation systems and specialized software applications with MATLAB.

Big data and image analysis in downstream energy

Development of CRM for Reservoir Simulations Using PINNs

Discover how Chevron supports real-time decision-making during oil and gas production monitoring with reduced-order modeling, simulation, and machine learning in MATLAB.

Microseismic Digitalization at the Quest CCS Facility

See how Shell performs large-scale microseismic monitoring of a carbon capture and storage (CCS) process using an integrated app developed in MATLAB.

Accelerate Radar Simulations on NVIDIA GPUs Using GPU Coder

Learn how Shell automates image predictive analytics for event detection in chemical plants using deep learning and high-performance computing in MATLAB.