Physical Models for Predicting Hydraulic Fracture Productivity
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Solution Overview
Problem
Current methods for predicting hydraulic fracture treatment effectiveness in oil and gas reservoirs are inadequate, as they rely on empirical correlations and cannot accurately predict productivity in areas with limited well log and core data, failing to provide reliable results for both existing and future wells.
Innovation Solution
The development of physical models calibrated with laboratory rock sample data and shear sonic measurements, integrating petrophysical and mechanical rock properties analysis, allows for the prediction of recoverable hydrocarbons in wells without sophisticated measurements, enabling more comprehensive and confident predictions across conventional and unconventional reservoirs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If empirical correlation methods are used to predict productivity, then the method is simple to implement, but the prediction accuracy and confidence are insufficient
Solution Approach 1:
The patent introduces physical models as an intermediary between empirical correlations and productivity prediction. These models incorporate rock mechanics properties, mineralogy, and geomechanical stress fields to bridge the gap between simple empirical methods and accurate predictions, enabling the use of basic well log data to achieve prediction accuracy previously only attainable with sophisticated measurements
Solution Approach 2:
The patent transforms the prediction approach by changing from purely empirical parameter correlations to physics-based parameter relationships. By incorporating rock strength, brittleness, and stress field parameters into the prediction model, the system achieves higher prediction accuracy while maintaining computational efficiency and ease of implementation
2Measurement precision
If sophisticated measurements (core analysis, sonic data) are used, then prediction accuracy is improved, but the coverage of wells that can be analyzed is limited
Solution Approach 1:
The patent develops physical models that serve multiple functions: they can process both sophisticated measurements (when available) and basic well log data (when sophisticated measurements are absent). This universal approach enables the same modeling framework to be applied across all wells in a project area, significantly expanding well coverage while maintaining prediction accuracy
Solution Approach 2:
The patent creates virtual representations of rock properties and stress fields that can be propagated from wells with sophisticated measurements to wells with only basic logs. By copying and adapting the physical model framework across different data quality levels, the system achieves consistent prediction accuracy across the entire project area
3Measurement precision
If physical models calibrated with laboratory data and sonic measurements are developed, then prediction accuracy and coverage are improved, but the model complexity increases
Solution Approach 1:
The patent segments the complex prediction problem into distinct physical components: rock mechanics properties, mineralogy effects, stress field characterization, and fracture propagation physics. By dividing the overall model into these manageable segments, the system achieves high prediction accuracy through physics-based relationships while maintaining computational tractability and model interpretability
Data Source
AI summary
Predicting hydraulic fracture treatment uses well log data and core data from one well in a given subsurface region to create a petrophysical properties model for the subsurface region. The petrophysical properties model yields fluid volumes and mineral volumes in any given well passing through the subsurface region using only well log data as inputs. The fluid and mineral volumes are used with dipole sonic data from a second well to create an elastic rock properties model for the given subsurface that yields elastic properties in any well passing through the subsurface region using only well log data and mineral and fluid volumes. For wells in the subsurface having only well log data, the petrophysical properties model and the elastic rock properties model are used with the well log data to predict an amount of recoverable hydrocarbons within wells that will respond to hydraulic fracture treatments.