Fracture Geometry Evaluation Using Cross-Well Strain Inversion
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Solution Overview
Problem
The challenge in understanding the key drivers behind artificially induced fracture networks in unconventional wells during hydraulic fracturing remains due to subsurface complexities and the interdependence of completion design variations, limiting the effectiveness of distributed fiber-optic sensing techniques in providing quantitative analysis for fracture geometry and hydraulic fracturing efficiency.
Innovation Solution
A method utilizing cross-well strain measurements with an inversion algorithm to calculate fracture width and height, integrated into a statistical model, employing Bayesian inference and Monte Carlo simulation to generate a distribution of possible fracture geometries, accounting for both observed and unobserved fractures, and providing metrics for production and economic efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If cross-well distributed strain measurements are used to characterize fracture geometry, then measurement capability is improved, but quantitative analysis and interpretation remain insufficient
Solution Approach 1:
The patent introduces an inversion algorithm as an intermediary tool that transforms raw cross-well distributed strain measurements into quantitative fracture geometry parameters. This algorithm acts as a mediator between the measurement system and the interpretation process, enabling the extraction of meaningful quantitative information (fracture width, height, length, orientation) from the strain data without losing critical diagnostic capabilities
Solution Approach 2:
The patent replaces qualitative mechanical interpretation methods with a computational inversion algorithm that processes strain measurements mathematically. This substitution transforms the analysis from subjective qualitative assessment to objective quantitative calculation, allowing precise determination of fracture geometry parameters while maintaining full diagnostic information
2Productivity
If completion design variations are increased to optimize resource access, then productivity is improved, but understanding key drivers becomes more difficult
Solution Approach 1:
The patent implements a feedback mechanism where cross-well distributed strain measurements provide real-time information about fracture propagation in response to completion design variations. This feedback loop allows operators to understand the actual impact of design changes on fracture geometry and resource access, enabling data-driven optimization that reduces complexity by identifying which design parameters actually drive productivity
Solution Approach 2:
The patent systematically varies completion design parameters (fluid volume, proppant concentration, injection rate) and uses the inversion algorithm to quantify their individual impacts on fracture geometry. By changing parameters in a controlled manner and measuring the responses, the patent identifies key drivers that truly affect resource access, allowing optimization without unnecessary complexity
3Area of stationary object
If distributed fiber-optic sensing is deployed for monitoring, then measurement coverage is improved, but quantitative interpretation of fracture geometry remains limited
Solution Approach 1:
The inversion algorithm serves as an intermediary that bridges the gap between the extensive spatial coverage of distributed fiber-optic sensing and quantitative fracture geometry interpretation. It processes the distributed strain measurements along the entire fiber length and transforms them into meaningful fracture parameters, preserving all quantitative information from the wide-area monitoring coverage
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
Enables accurate and comprehensive evaluation of fracture geometries, improving production forecasts and optimizing hydraulic fracturing designs by integrating statistical model outputs with production prediction methods, reducing uncertainty and cost in well completion.
Implementation Method 1
Distributed fiber-optic sensing (DFOS) is a class of sensing techniques that has become available within the last decade for monitoring the completion and production of unconventional wells. DFOS effectively turns a length of fiber-optic cable into a linear network of sensors that are sensitive to mechanical strain, vibration, and temperature variations along the length of a wellbore.
Implementation Method 2
A method utilizing cross-well strain measurements with an inversion algorithm to calculate fracture width and height, integrated into a statistical model, employing Bayesian inference and Monte Carlo simulation to generate a distribution of possible fracture geometries
Implementation Method 3
A method utilizing cross-well strain measurements with an inversion algorithm to calculate fracture width and height, integrated into a statistical model, employing Bayesian inference and Monte Carlo simulation to generate a distribution of possible fracture geometries
Data Source
AI summary
An improved fracking efficiency evaluation system and method of the system can be implemented to generate a completion design plan based on quantitative analysis of fracture geometries including observed and unobserved fractures in a treatment well. One or more metrics based on a statistical distribution of fracture geometries of an entire treatment well including each stage can be used to generate a completion design plan for optimizing performance of a treatment well.