Real-time Diverter Placement Control for Multistage Stimulation
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Solution Overview
Problem
Conventional hydraulic fracturing techniques fail to accurately monitor and control the downhole flow distribution of injected fluids during multistage stimulation treatments, leading to inefficient use of resources and suboptimal hydrocarbon recovery.
Innovation Solution
Implementing real-time monitoring and control systems that use data from sensors and diagnostic tools to adjust the deployment of diverter materials, allowing for dynamic adjustments to the treatment schedule to optimize fluid distribution and perforation cluster efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional predefined treatment schedules are used for diversion, then operational simplicity is maintained, but downhole flow distribution uniformity deteriorates
Solution Approach 1:
The patent implements real-time monitoring of downhole flow distribution and uses this feedback to dynamically adjust diverter placement decisions. Sensors measure actual flow at different wellbore locations, and this data feeds back to control systems that modify treatment schedules accordingly, resolving the contradiction between operational simplicity and flow distribution uniformity.
Solution Approach 2:
The patent transitions from static predefined treatment schedules to dynamic adaptive scheduling based on real-time downhole conditions. The treatment plan is continuously adjusted during execution based on monitored flow distribution, allowing the system to adapt to actual operating conditions while maintaining operational feasibility.
2Manufacturing precision
If real-time monitoring and dynamic adjustment systems are implemented, then downhole flow distribution uniformity is improved, but system complexity increases
Solution Approach 1:
The patent integrates multiple functions into unified downhole tools and surface systems. The monitoring system serves multiple purposes: measuring flow distribution, detecting downhole conditions, and providing data for treatment optimization. This multi-functionality reduces the need for separate dedicated systems, thereby limiting the increase in overall system complexity.
Solution Approach 2:
The patent introduces intermediate processing layers including data acquisition systems, interpretation algorithms, and decision support tools that bridge the gap between raw sensor data and control actions. These intermediaries simplify the complexity by organizing and processing information in manageable stages rather than requiring direct complex interactions between all system components.
3Productivity
If conventional diversion techniques are used without real-time monitoring, then treatment time is reduced, but hydrocarbon recovery efficiency deteriorates
Solution Approach 1:
The patent performs preliminary assessments and predictions of downhole flow distribution before executing diversion actions. By anticipating flow patterns and identifying potential issues in advance, the system can make proactive adjustments that improve recovery efficiency without requiring extensive trial-and-error iterations that would extend treatment time.
Solution Approach 2:
The patent maintains continuous monitoring and adjustment throughout the treatment process, ensuring that useful actions (fluid injection and diverter placement) are continuously optimized. This continuous optimization improves overall recovery efficiency without requiring interruptions or repeated treatments, thereby limiting time loss.
Data Source
AI summary
System and methods of controlling diverter placement during stimulation treatments are provided. Data relating to at least one downhole parameter is obtained for a current treatment stage within a subsurface formation. A response of the diverter to be injected during a diversion phase of the current stage on the downhole parameter is estimated, based on the obtained data and a diagnostic data model. Values for diversion control parameters are calculated, based on the estimated response. As the diverter is injected into the formation, an actual response of the diverter is monitored. Upon determining that a difference between the actual and estimated response exceeds an error tolerance threshold, the model is updated. The model is further updated over subsequent iterations of the diversion phase when the actual response is less than the estimated response. Subsequent diversion phases are performed over a remainder of the current stage, based on the updated model.