Fracture Volume Prediction via Real-Time Event Categorization
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Solution Overview
Problem
Conventional hydraulic fracturing techniques fail to provide optimal information on fracture efficiency and production potential, as they do not differentiate between various types of fractures and their likelihood to produce oil and gas.
Innovation Solution
A programmable processing system that analyzes real-time and historical data streams from well-pressure measurements, fluid flow, and sand injection to categorize fracturing events into types, including long fractures, complex fractures, sand-induced fractures, and natural micro-fracture expansions, enabling precise fracture volume assessment and prediction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional techniques are used to determine total rock fractures, then the total fracture count is obtained, but the differentiation between fracture types and their production potential is lost
Solution Approach 1:
The patent segments the homogeneous fracture detection into four distinct fracture type categories (Type I: long rapidly occurring fractures, Type II: complex rapidly occurring fractures with pressure drop and recovery, Type III: sand-induced fractures from high stress, Type IV: natural micro-fracture expansions). This segmentation allows differentiation between fracture types while maintaining comprehensive monitoring, directly resolving the information loss problem.
2Reliability
If real-time monitoring of all fracturing parameters is implemented, then comprehensive fracture data is obtained, but the system complexity and cost increase
Solution Approach 1:
The patent employs a multi-functional data acquisition system that simultaneously monitors multiple parameters (pressure, flow rate, sand injection rate, temperature) using integrated sensors and a centralized processing unit. This universal system handles diverse measurement tasks through a single coordinated platform, reducing overall system complexity while maintaining comprehensive data collection for reliable fracture assessment.
Solution Approach 2:
The patent introduces a programmable processing system as an intermediary that receives, integrates, and analyzes data from multiple sensor sources. This intermediary component consolidates complex data streams into processed information about fracture type and volume, simplifying the interface between raw sensor data and decision-making processes while maintaining system reliability.
3Productivity
If traditional fracture monitoring methods are used, then the process is simple, but the ability to predict production and optimize fracturing operations is limited
Solution Approach 1:
The patent implements a feedback mechanism where real-time monitoring data on fracture type, volume, and characteristics is continuously fed back to the fracturing operation control system. This feedback enables dynamic adjustment of injection parameters to optimize fracture creation while predicting production outcomes, directly enhancing productivity through data-driven decision making.
Solution Approach 2:
The patent applies preliminary action by using real-time fracture monitoring data to predict future production outcomes and potential screen-outs before they occur. The system analyzes accumulating fracture volume and type information during the fracturing process to forecast production potential and prevent operational problems in advance, enabling proactive optimization rather than reactive response.
Data Source
AI summary
A system for assessing the characteristics of one or more geological formations that includes a programmable processing system configured receive at least one data stream including (1) a stream of well-pressure measurements, where each item of well-pressure measurement data corresponds to the pressure within the geological formation at a given time, (2) a stream of data associated with the flow of water and/or slurry into the geological formation at different times, and (3) a stream of data associated with the flow of sand into the geological formation at different times, where the programmable processing system is further configured to categorize fracturing events into different categories.