Formation Analysis via Rock Type Probability Segmentation
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Solution Overview
Problem
Current formation models, such as three-dimensional lithology models, often lack sufficient resolution and accuracy in representing rock content and physical properties, leading to inaccuracies in fluid flow models and requiring significant edits and assumptions by reservoir engineers.
Innovation Solution
A system and method that partition a formation into sections, determine the probability of different rock types present in each section using multiple lithological analyses, assign values based on these probabilities, and blend properties to generate improved models for fluid flow and hydrocarbon resource estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional three-dimensional lithology models are used, then the overall structure of the formation can be represented, but the resolution and accuracy of rock content and physical properties are insufficient
Solution Approach 1:
The formation is divided into multiple sections along vertical intervals, with each section analyzed independently through multiple lithological analyses. This segmentation allows for higher resolution representation of rock content while maintaining manageable complexity through systematic processing of each section.
Solution Approach 2:
The patent transitions from traditional single-value lithology models to a multi-dimensional probability framework. Each formation section is characterized by probability values from multiple lithological analyses, adding a probabilistic dimension that enhances accuracy without requiring complete redesign of the modeling approach.
2Reliability
If formation models are based on poorly resolved rock properties, then the modeling process is simpler, but fluid flow models require drastic edits and broad assumptions
Solution Approach 1:
Multiple lithological analyses are performed in advance on each formation section to determine probability values before fluid flow modeling. This preliminary action provides accurate rock property representation that reduces the need for later edits and assumptions in fluid flow model generation.
Solution Approach 2:
The system uses probability values from multiple lithological analyses as feedback to guide fluid flow model generation. These probability-based rock property representations provide a foundation that reduces discrepancies between modeled and observed fluid flow behavior.
3Measurement precision
If multiple lithological analyses are performed to determine probability of rock types, then the accuracy of rock content representation improves, but the analysis complexity increases
Solution Approach 1:
The formation is segmented into vertical sections, and multiple lithological analyses are applied to each section independently. This segmentation allows systematic execution of multiple analyses while managing complexity through modular processing of individual sections.
Solution Approach 2:
The patent changes the output parameter from single deterministic rock type assignments to probabilistic values ranging from 0 to 100. This parameter transformation allows multiple lithological analyses to be synthesized into a unified probability framework that enhances accuracy while providing interpretable results.
Data Source
AI summary
Systems and methods to assess formation data are disclosed. The method includes partitioning a formation containing a plurality of rock types into a plurality of sections. For a section of the plurality of sections, the method also includes determining, for each rock type of the plurality of rock types, a probability that the rock type is present in the section. The method further includes assigning a value to the section of the plurality of sections based on a probability that the section contains one or more rock types of the plurality of rock types. The method further includes analyzing the formation based on the value associated with the section.