Dynamic Reservoir Earth Model for Real-Time Hydrocarbon Estimation
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Solution Overview
Problem
Current methods for generating and updating subsurface reservoir models in hydrocarbon exploration are inefficient, as they rely on static data analysis and lack real-time adaptation, leading to inaccurate hydrocarbon reserve estimations and suboptimal well placement.
Innovation Solution
An integrated methodology employing machine learning and artificial intelligence to process seismic data, generating and updating multi-dimensional geological models using predictive models that adapt continuously, enabling real-time optimization of hydrocarbon exploration processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional static data analysis methods are used for generating subsurface reservoir models, then the process is simpler to implement, but the accuracy of hydrocarbon reserve estimations deteriorates due to lack of real-time adaptation
Solution Approach 1:
The patent implements dynamic updating of the subsurface reservoir model by continuously integrating new seismic data and well log data. The model transitions from a static representation to a dynamic one that adapts in real-time as new information becomes available during drilling operations, thereby improving the accuracy of hydrocarbon reserve estimations without requiring complete re-modeling
Solution Approach 2:
The system incorporates feedback mechanisms where well log data and seismic data acquired during drilling operations are fed back into the reservoir model. This feedback loop allows the model to be continuously refined and updated, improving estimation accuracy by incorporating actual measurements from the drilling process itself
2Manufacturing precision
If static data analysis is used for well placement planning, then the planning process is faster to complete, but the precision of well placement deteriorates due to inability to adapt to new information
Solution Approach 1:
The system performs preliminary well placement planning based on initial reservoir models before drilling begins. This allows planners to identify optimal well locations in advance while the model is still being refined, enabling parallel processing of model updates and well placement decisions to minimize time loss
Solution Approach 2:
The well placement recommendations are dynamically adjusted as the reservoir model updates with new data. The system can rapidly re-evaluate and suggest alternative well placements if new seismic or well log data indicates changes in reservoir characteristics, maintaining high precision without requiring complete replanning
3Adaptability or versatility
If traditional reservoir modeling approaches are used, then the analytical rules remain stable and predictable, but the adaptability to new seismic data and geological variations deteriorates
Solution Approach 1:
The analytical rules in the reservoir model are designed to be dynamically adjustable. As new seismic data and well log data are incorporated, the model parameters and analytical relationships can be refined to better reflect actual subsurface conditions, allowing the system to adapt to geological variations while maintaining a structured framework
Solution Approach 2:
The reservoir model is segmented into multiple independent components including seismic data processing, well log integration, and hydrocarbon estimation modules. This segmentation allows individual analytical rules to be updated and refined independently without destabilizing the entire model, maintaining overall stability while enabling local adaptability
Data Source
AI summary
Methods and systems, including computer programs encoded on a computer storage medium can be used for an integrated methodology that can be used by a computing system to automate processes for generating, and updating (e.g., in real-time), subsurface reservoir models. The methodology and automated approaches employ technologies relating to machine learning and artificial intelligence (AI) to process seismic data and information relating to seismic facies.