AI Lithology Compositional Model for Subsurface Formation Evaluation

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Solution Overview

Problem

Traditional methods for determining subterranean formation lithology and mineralogy are inefficient and limited in providing high-resolution, directional measurements, often relying on core analysis and are prone to errors due to non-unique solutions from compositional colinearity, especially when attempting to quantify minerals without prior knowledge of their presence.

Innovation Solution

The use of an artificial intelligence system that generates lithology and mineralogy compositional models from elemental measurements obtained from downhole tools, such as pulsed neutron devices, to define the general and specific lithology and mineralogy of a subterranean formation, incorporating additional data sources like NMR, resistivity, and gamma-ray data to improve accuracy.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If traditional core analysis methods are used to determine lithology and mineralogy, then measurement accuracy can be achieved, but the process is very time-consuming and inefficient

Engineering Contradiction:

Improvelithology and mineralogy determination accuracyVSAvoidevaluation efficiency

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

The patent replaces traditional mechanical core analysis methods with nuclear physics-based logging tools (neutron and gamma-ray spectrometers) that perform remote, in-situ measurements of formation mineralogy and lithology, eliminating the need for physical core retrieval and laboratory analysis while maintaining quantitative accuracy

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent creates virtual models of formation mineralogy and lithology by transforming logging tool measurements into compositional models that replicate the information obtained from physical core analysis, enabling efficient evaluation without direct physical sampling

Inventive Principle:

Principle #26Copying

2Productivity

If logging tools are used to estimate lithology and mineralogy, then evaluation efficiency is improved, but measurement precision deteriorates due to non-unique solutions from compositional colinearity

Engineering Contradiction:

Improveevaluation efficiencyVSAvoidmineralogy quantification accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The patent introduces compositional colinearity as an intermediary constraint in the inverse problem formulation, using it to stabilize the mathematical solution and eliminate non-unique solutions that arise from the ill-posed nature of transforming logging measurements into mineralogy estimates

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent transforms the measurement parameters from raw logging tool responses into compositional models that represent formation mineralogy and lithology, using mathematical transformations that account for the physical interactions between neutron/gamma-ray sources and formation materials

Inventive Principle:

Principle #35Parameter changes

3Device complexity

If traditional logging methods are used, then equipment complexity is low, but the ability to provide directional measurements and high-resolution data is limited

Engineering Contradiction:

Improvelogging system simplicityVSAvoidvertical and lateral resolution

Core Design Contradiction:

Device complexityVSMeasurement precision

Solution Approach 1:

The patent transitions from traditional point-measurement logging to three-dimensional compositional modeling by incorporating directional measurement capabilities and spatially distributed sensing, enabling high-resolution characterization of formation properties in multiple dimensions simultaneously

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

This approach enables more accurate and efficient determination of subterranean formation mineralogy and lithology, reducing errors associated with traditional methods and providing detailed geological information with improved resolution and directional capability.

Implementation Method 1

elemental measurements obtained from downhole tools, such as pulsed neutron devices

Methodology Applied

Scientific EffectNeutron interaction:

Implementation Method 2

gamma-ray data

Methodology Applied

Scientific EffectGamma-ray spectroscopy:

Data Source

PatentUS8101907B2Methods for quantitative lithological and mineralogical evaluation of subsurface formations

Publication Date: 2012.01.24 BAKER HUGHES CO

AI summary

Methods, systems, apparatus and processes for determining the lithology as well as the mineralogy of subterranean formations surrounding a borehole are described. According to the methods and processes, well log data measurements from neutron spectroscopy applications and associated tool response parameters are solved using an artificial intelligence system, such as an expert system, which in turn generates an appropriate discriminator and/or compositional model that estimates both general and specific lithology as well as the mineralogy constraints of the subterranean formation being analyzed. The methods exhibit good elemental correlation between conventional methods of lithology and mineralogy determination, and can provide numerous output data, including grain density and porosity data within zones of the formation.