3D Fracture Network Model From Acoustic Wellbore Signals
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Solution Overview
Problem
Current deep wave imaging (DWI) methods are limited in accurately detecting the size, scale, and extent of fracture networks, as well as their spatial characteristics, which hinders the creation of detailed three-dimensional models necessary for hydrocarbon exploration and production, particularly in reservoir and fracture modeling workflows.
Innovation Solution
A method and system for generating a three-dimensional fracture network model by processing reflected acoustic signal measurements from sensors in a wellbore, involving fracture extension estimates and intensity thresholds to suppress noise, allowing for more precise characterization and modeling of fracture networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If deep wave imaging (DWI) data is used to detect fracture presence, then fracture detection capability is improved, but fracture network characterization precision deteriorates
Solution Approach 1:
The patent segments the fracture detection and characterization process into multiple stages: initial DWI data acquisition for fracture presence detection, followed by separate acquisition of additional acoustic measurements at multiple frequencies and angles, and finally integrated processing to generate comprehensive 3D fracture network models. This segmentation allows each stage to optimize for its specific purpose while contributing to overall characterization precision.
Solution Approach 2:
The patent transitions from 2D DWI data to 3D fracture network models by acquiring acoustic measurements at multiple frequencies, angles, and spatial locations. This dimensional expansion adds depth, orientation, and spatial distribution information that enables precise characterization of fracture networks while building upon the initial fracture detection capability.
2Loss of information
If three-dimensional models are created from seismic data, then model comprehensiveness is improved, but measurement precision deteriorates
Solution Approach 1:
The patent merges multiple types of acoustic measurement data (different frequencies, angles, and spatial locations) with DWI data to create integrated 3D fracture network models. This combination preserves the comprehensive spatial information from seismic data while enhancing fracture characterization precision through the addition of high-resolution acoustic measurements taken from multiple perspectives.
Solution Approach 2:
The patent creates a composite data model that integrates DWI data, multi-frequency acoustic reflections, and multi-angle measurements. This composite approach combines the advantages of each data type: the broad coverage of seismic DWI data with the high precision of targeted acoustic measurements, resulting in both comprehensive coverage and precise fracture characterization.
3Adaptability or versatility
If stochastic methods are used to generate three-dimensional models, then model generation flexibility is improved, but solution certainty deteriorates
Solution Approach 1:
The patent incorporates iterative feedback loops in the model generation process where initial 3D models are generated, compared against the actual multi-frequency and multi-angle acoustic measurement data, and refined accordingly. This feedback mechanism maintains flexibility in model generation while improving solution certainty by continuously validating and adjusting models against empirical data.
Solution Approach 2:
The patent employs dynamic model generation that adapts to the specific characteristics of the measured data. Rather than using fixed stochastic algorithms, the system dynamically adjusts model parameters and structures based on the actual fracture patterns detected in the acoustic data, maintaining flexibility while ensuring solutions are grounded in observed evidence for greater certainty.
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 provides hydrocarbon operators with enhanced insights into fracture network presence, location, and characteristics, enabling more efficient resource allocation and improved modeling in hydrocarbon exploration and production, while being more readily usable in reservoir and fracture modeling workflows.
Implementation Method 1
transmitting acoustic signals, from a sensor, such as a transducer, disposed in a borehole located within a target region to be evaluated. The acoustic signals transmitted from the transducer generate seismic body waves that radiate away from the borehole
Implementation Method 2
The acoustic signals transmitted from the transducer generate seismic body waves that radiate away from the borehole and are reflected back to the sensor by the hydrocarbon sources or various earth formations
Data Source
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AI summary
Systems, methods, and computer-readable medium for generating a three-dimensional fracture network model are provided. The method can include receiving reflected acoustic signal measurements acquired in response to emission of acoustic waves by one or more sensors disposed in a wellbore formed within a target region. Each reflected acoustic signal measurement represents a strength of a reflected acoustic wave as a function of time measured in at least one predetermined direction oriented with respect to an axis of the wellbore. A fracture extension estimate is generated for each of the reflected acoustic signal measurements. A three-dimensional fracture network model is generated corresponding to the fracture extension estimates generated for each of the plurality of reflected acoustic measurements. The generated fracture network model is output for display or use in modeling environments.