Borehole Acoustic Inversion in Anisotropic Formations

Resolve Bottlenecks,
Find Innovative Solutions
Generate Solutions

Solution Overview

Problem

Simulating borehole acoustic properties in anisotropic formations of the Earth's crust is computationally exhaustive, making real-time analysis during drilling challenging due to the complexity required to capture physical mechanisms accurately.

Innovation Solution

A method that formulates a geometric model in cylindrical coordinates, represents field variables as Fourier series expansions of π-periodic harmonics, and numerically solves three-dimensional wave equations, allowing for efficient computation and inversion of elastic properties, even in cases with material anisotropy that violates axis-symmetry conditions.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If full 3-dimensional finite element modeling is used to simulate borehole acoustic problems in anisotropic formations, then the accuracy and capability to capture physical mechanisms is improved, but the computational complexity and resource requirements become prohibitive for real-time logging while drilling applications

Engineering Contradiction:
Improveaccuracy of acoustic property simulationVSAvoidcomputational complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The patent transforms the 3D wave propagation problem in cylindrical coordinates into a 2D problem by applying Fourier series expansion in the circumferential direction. This dimensionality reduction converts the computationally intensive 3D finite element model into a more efficient 2D model that retains accuracy for anisotropic formations while reducing computational complexity suitable for real-time logging applications.

Inventive Principle:
Principle #17Another dimension (Dimensionality change)

2Adaptability or versatility

If standard three dimensional isoparametric finite elements are used to model layer by layer variations in elastic parameters and anisotropy, then the ability to capture complex physical mechanisms is improved, but the computational time and resources become exhaustive and prohibitive

Engineering Contradiction:
Improvecapability to model anisotropy and layer variationsVSAvoidcomputational efficiency
Core Design Contradiction:
Adaptability or versatilityVSProductivity

Solution Approach 1:

The patent reduces the 3D computational problem to 2D by utilizing the cylindrical geometry and applying Fourier series in the circumferential direction. This allows the model to handle layer-by-layer anisotropic variations efficiently without requiring exhaustive 3D finite element computations, thus improving productivity while maintaining adaptability to complex formation properties.

Inventive Principle:
Principle #17Another dimension (Dimensionality change)

Solution Approach 2:

The patent changes the mathematical representation of the wave equation by applying Fourier series expansion in the circumferential direction and using cylindrical coordinates. This parameter transformation converts the complex 3D anisotropic problem into a more tractable 2D problem that can be solved efficiently while preserving the ability to model layer variations and anisotropy.

Inventive Principle:
Principle #35Parameter changes

3Reliability

If complex computational models are used to accurately simulate acoustic wave propagation in anisotropic formations, then the reliability of inversion results is improved, but the computational time increases making real-time analysis difficult

Engineering Contradiction:
Improvereliability of elastic property inversionVSAvoidcomputational time
Core Design Contradiction:
ReliabilityVSLoss of time

Solution Approach 1:

The patent applies Fourier series expansion in the circumferential direction to transform the 3D wave propagation problem into a 2D problem. This dimensionality reduction maintains the reliability of inversion results by preserving the essential physics of anisotropic wave propagation while significantly reducing computational time to enable real-time logging while drilling applications.

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 high computational efficiency for real-time analysis of logging data while drilling, facilitating the determination of physical properties like elastic properties, velocity, density, and porosity, even in formations with varying anisotropy, by reducing the dimensionality of integrals and leveraging π-periodicity in the circumferential direction.

Implementation Method 1

the one or more field variables are represented as respective Fourier series expansions of π-periodic harmonics in the circumferential direction

Methodology Applied
Scientific EffectFourier series expansion:

Data Source

PatentUS9557442B2Borehole seismic inversion in anisotropic formation
Publication Date: 2017.01.31 TOTAL E&P DANMARKS AS
  • US9557442B2 patent drawing
  • US9557442B2 patent drawing
  • US9557442B2 patent drawing

AI summary

A method of simulating a borehole acoustic response in an anisotropic formation of the crust of the earth includes formulating a geometric model of the formation. The geometric model includes a plurality of layers definable in a cylindrical coordinate system defined by an axial direction normal to each of the layers, a radial direction relative to the axial direction, and a circumferential direction relative to the axial direction. The method also includes formulating a computational model of wave propagation in the formation. The computational model includes field variables and a wave equation describing a behavior of the field variables. The field variables are represented as respective Fourier series expansions of Tr-periodic harmonics in the circumferential direction. The method also includes numerically solving the computational model.