Expertise in Hydraulic Fracturing, Geomechanics, Reservoir Engineering and Data Science/ML to Optimize Hydrocarbon Recovery
55% of poor stimulation performance is due to a poor understanding of the subsurface reservoir* - even larger than due to poor reservoir quality itself (10%)*. Understanding the reservoir and optimum completion strategies is critical to optimizing Hydrocarbon recovery.
Pressure Transient Analysis (PTA) to correctly estimate reservoir parameters, Rate Transient Analysis (RTA) for EUR estimation. Accurate reservoir modeling & simulation for parameter sensitivity, well spacing and fracture spacing studies is essential. Understanding of the assumptions made is critical to validate the analysis.
When physics based models do not work, Artificial Intelligence (AI) and Machine Learning (ML), where the "data decides the model", has been found to be beneficial. However, care should be taken to ensure that AI is not blindly applied. It is here that symbiotic intelligence is required, i.e., AI & ML with domain expertise.
Typical workflow for unconventionals includes building reservoir model from well logs, designing / modeling hydraulic fractures and history matching the production by varying the fracture and reservoir parameters. "Quick estimations", "shortcuts" & "AI/ML" can be used for these processes.