Automated Rock Physics Modeling via Inverse Problem Solutions

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Solution Overview

Problem

Current methods for quantitatively analyzing rock mechanical properties are inaccurate and require significant expertise, limiting their application and impacting the predictive capabilities of technologies like hydraulic fracturing.

Innovation Solution

A computer-implemented method for automated rock physics modeling that preprocesses data from logging tools, uses automated procedures to determine optimal parameters for rock physics models, and computes mechanical properties, including Poisson's ratio and bulk modulus, through a series of local inversions and forward runs.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If advanced rock physics models are used to improve accuracy of rock mechanical properties, then measurement precision improves, but device complexity increases

Engineering Contradiction:

Improveaccuracy of rock mechanical propertiesVSAvoidcomplexity of rock physics models

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system performs automated self-calibration by using the logging tools to measure rock properties and automatically adjusting model parameters through iterative inversion processes, eliminating the need for manual expert intervention while maintaining high accuracy

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The complex rock physics modeling process is divided into discrete automated steps: data acquisition from logging tools, parameter estimation, iterative inversion, and property calculation, allowing each segment to be processed systematically by computer algorithms

Inventive Principle:

Principle #1Segmentation

2Reliability

If manual parameter adjustment by practitioners is used to solve inverse problems, then ease of operation decreases, but reliability improves

Engineering Contradiction:

Improvequality of predictionsVSAvoidease of parameter adjustment

Core Design Contradiction:

ReliabilityVSEase of operation

Solution Approach 1:

The manual mechanical process of parameter adjustment by practitioners is replaced with an automated computational system that uses computer algorithms to perform iterative inversion and determine optimal parameters, eliminating human subjectivity while maintaining reliability

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system implements automated feedback loops where the forward model predictions are compared with actual logging data, and parameter adjustments are made iteratively based on the difference between predicted and measured values, ensuring reliable results without manual intervention

Inventive Principle:

Principle #23Feedback

3Device complexity

If field dependent correlations are used for quantitative analysis, then device complexity decreases, but measurement precision worsens

Engineering Contradiction:

Improvesimplicity of analysis methodVSAvoidaccuracy of rock mechanical properties

Core Design Contradiction:

Device complexityVSMeasurement precision

Solution Approach 1:

The system transitions from using fixed field-dependent correlation parameters to dynamically determining model parameters through automated inversion processes, allowing parameters to be optimized for each specific geological formation while maintaining computational efficiency

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS10139519B2Method for automated rock physics modeling

Publication Date: 2018.11.27 EXXONMOBIL UPSTREAM RESEARCH COMPANY(US)

AI summary

A computer-implemented method for automated rock physics modeling. The method includes the steps of (a) pre-processing data obtained from a suite of logging tools over a range of depths; (b) using an automated, computer-implemented procedure to determine a solution to an inverse problem associated with the rock physics model using the data from step (a), the solution including a list of optimal parameters; (c) performing a forward run of the rock physics model; and (d) computing a set of rock mechanical properties using the optimal parameters obtained in step (b). A computer program product for automated rock physics modeling is also provided.