Geological Database Signatures for Hydrocarbon Exploration
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Solution Overview
Problem
Hydrocarbon exploration faces challenges in quickly and accurately identifying analogous subterranean formations due to incomplete subsurface information and the computational intensity of multi-parameter searches in geological databases, leading to biased selection and inefficient modeling.
Innovation Solution
A contextual geological database is configured to use parameter spaces or signatures extracted from geological features of interest, allowing for automated or manual identification of analogous formations through unsupervised machine learning, leveraging parameters such as wave energy, subsidence rates, and eustasy to generate robust subsurface models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multi-parameter search is performed to identify analogous formations, then matching accuracy is improved, but search time and computational demand increase significantly
Solution Approach 1:
The patent segments the formation description into discrete standardized elements (lithology, porosity, permeability, saturation, etc.) that can be independently compared. This segmentation allows the search algorithm to efficiently evaluate multiple parameters without treating them as a monolithic complex comparison, thereby reducing computational overhead while maintaining matching accuracy.
Solution Approach 2:
The patent transforms geological parameters into standardized quantitative formats with defined units and ranges. By normalizing parameters such as porosity (volume fraction), permeability (Darcy units), and saturation (fraction), the system enables efficient algorithmic comparison across diverse data sources without losing geological nuance, thus improving search speed while preserving matching precision.
2Reliability
If comprehensive geological data is collected for accurate formation comparison, then model reliability is improved, but data processing complexity increases
Solution Approach 1:
The patent creates a universal data framework that handles multiple types of geological parameters (lithological, petrophysical, geometric, fluid properties) through a single standardized element structure. This multi-functional framework eliminates the need for separate processing pipelines for different data types, reducing overall system complexity while maintaining comprehensive data analysis for reliable modeling.
Solution Approach 2:
The patent uses template-based formation models that capture essential geological structures and properties. These templates serve as reusable copies that can be instantiated with specific parameter values from different formations, allowing accurate comparisons without reprocessing entire datasets each time, thus reducing processing complexity while maintaining model reliability.
3Measurement precision
If detailed formation parameters are used for searching, then analogy accuracy is improved, but database search efficiency decreases
Solution Approach 1:
The patent performs preliminary indexing of formation parameters during data entry, organizing geological data into standardized elements with pre-computed characteristics. This preliminary structuring allows the search algorithm to quickly retrieve and compare relevant parameters without processing raw data during the actual search, thereby maintaining high analogy accuracy while improving search efficiency.
Solution Approach 2:
The patent extracts only the essential comparison parameters (lithology type, porosity range, permeability range, saturation values) from comprehensive formation data during the search process. By selectively extracting relevant elements rather than comparing all available data, the system maintains analogy accuracy for critical parameters while reducing the computational burden of the search operation.
Data Source
AI summary
A system is described for determining an analogue geological feature. The system may include a processor and a non-transitory computer-readable medium comprising instructions that are executable by the processor to cause the processor to perform various operations. The system may generate, by extracting parameter signatures for geological features, a database including parameters about geological features associated with parameter signatures. The system may receive data including parameters and a feature-type about a geological feature of interest. The system may generate a signature including values for a subset of the feature-of-interest parameters selected based on the geological feature of interest for the feature-of-interest using the data. The system may execute a comparison of the feature signature to the parameter signatures included in the database for identifying an analogue geological feature for the feature of interest. The system may output a subset of parameters for the analogue for use in subterranean exploration.