Numerical Analog Models for Geological Architecture Estimation
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Solution Overview
Problem
Current methods for estimating geological architecture in reservoir exploration are limited by the subjective nature of broad uncertainty models, which fail to reliably infer architectural parameters and ignore important expert knowledge, making them unsuitable for quantitative decision-making.
Innovation Solution
A computer-implemented method using numerical analogs to represent geological characteristics as a function of position, identifying interdependencies, and assigning probabilities of correspondence based on distributions and local compliance data to enhance the estimation of geological architecture.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If broad, naive uncertainty models are applied, then the process is simple, but the reliability and accuracy of geological architecture estimation deteriorates
Solution Approach 1:
The system performs preliminary actions by generating multiple numerical analog models that represent different possible geological architectures before actual reservoir exploration decisions are made. These pre-generated models incorporate various uncertainty scenarios and are evaluated against available data to identify the most probable architectural configurations, thereby reducing uncertainty before field operations begin.
Solution Approach 2:
The system creates simplified copies of complex geological systems through numerical analog models. These digital replicas mimic the behavior and characteristics of actual reservoirs, allowing researchers to test different architectural hypotheses and uncertainty scenarios without requiring expensive or time-consuming physical experiments or actual exploration.
2Device complexity
If local compliance data alone is used, then data acquisition is simple, but the ability to reliably infer architectural parameters deteriorates
Solution Approach 1:
The system merges multiple data sources and modeling approaches together. It combines local compliance data from wells with regional geological knowledge, numerical analog models, and uncertainty analysis frameworks. This integration creates a comprehensive evaluation system that leverages the strengths of each component while compensating for their individual limitations.
Solution Approach 2:
The system introduces numerical analog models as intermediary representations between raw compliance data and architectural parameter inference. These models act as mediators that translate discrete well data into continuous spatial predictions, incorporating geological principles and uncertainty quantification to bridge the gap between limited measurements and comprehensive architectural understanding.
3Device complexity
If expert knowledge is ignored, then the modeling process is simpler, but the quality of uncertainty models deteriorates
Solution Approach 1:
The system transforms qualitative expert knowledge into quantitative parameters that can be integrated into numerical models. Geological experts' insights about depositional environments, structural evolution, and reservoir behavior are converted into specific model parameters, boundary conditions, and probability distributions, allowing subjective expertise to objectively influence model outcomes.
Data Source
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AI summary
The geological architecture of a geologic volume of interest is estimated through the generation and/or selection of one or more numerical analog models of the geologic volume of interest that represent characteristics of the geologic volume of interest as a function of position within the geologic volume of interest. The estimation of geological architecture of the geologic volume of interest may be implemented in reservoir exploration and/or development.