Friction Factor Multiplier for Water Injection Network Calibration
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Solution Overview
Problem
Calibrating water injection network models in hydrocarbon extraction is challenging due to the need for accurate representation of field injection system performance, particularly in matching simulated pressure drops with measured drops across individual pipelines, which affects the detection of bottlenecks and optimization of injection strategies.
Innovation Solution
A method involving the determination of a friction factor multiplier to match simulated pressure drops with measured pressure drops at wellheads, by dividing the injection pipeline network into main-loops and sub-loops, and recalibrating the model using this multiplier to ensure accurate representation of field conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual calibration methods are used to match simulated pressure drops with measured pressure drops, then model accuracy can be improved, but the calibration process becomes time-consuming and labor-intensive
Solution Approach 1:
The system performs automatic calibration by having the computer automatically adjust friction factors and match simulated pressure drops with measured pressure drops without requiring manual intervention. The calibration process serves itself by using the measured data to automatically update the model parameters, eliminating the need for time-consuming manual calibration while maintaining high accuracy.
2Measurement precision
If detailed calibration of individual pipelines is performed to detect bottlenecks accurately, then bottleneck detection precision is improved, but the complexity of the calibration process increases
Solution Approach 1:
The injection pipeline network is divided into multiple individual pipelines or segments for separate calibration. Each pipeline's friction factor is adjusted independently based on its specific measured pressure drop data, allowing detailed bottleneck detection in each segment while managing complexity through systematic division of the overall calibration task.
Solution Approach 2:
The calibration process focuses on adjusting specific parameters (friction factors) for individual pipelines rather than recalibrating the entire network model. By changing only the necessary friction factor parameters for each pipeline segment, the system achieves accurate bottleneck detection while keeping the calibration process manageable and avoiding unnecessary complexity.
3Reliability
If friction factors are adjusted to match measured pressure drops, then model reliability is improved, but the number of adjustments and iterations required increases
Solution Approach 1:
The system uses measured pressure drop data as feedback to automatically adjust friction factors in the model. The computer compares simulated pressure drops with measured values and iteratively adjusts the friction factors until the match is satisfactory. This feedback mechanism ensures model reliability while automating the adjustment process to maintain productivity.
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 allows for the automatic calibration of water injection network models, improving their accuracy in representing field performance, enabling better detection of bottlenecks and optimization of injection strategies, thereby enhancing hydrocarbon extraction efficiency.
Implementation Method 1
determining a friction factor multiplier to match a simulated pressure drop in each of the plurality of sub-loops to a measured pressure drop at the wellhead
Data Source
AI summary
A method for calibrating a water injection network model includes obtaining measurements at a wellhead for a plurality of injection wells included in an injection pipeline network and determining an injection rate reconciliation for the plurality of injection wells. This method further includes dividing the injection pipeline network into a plurality of main-loops and subdividing the plurality of main-loops into a plurality of sub-loops. A friction factor multiplier is determined to match a simulated pressure drop in each of the plurality of sub-loops to a measured pressure drop at the wellhead and the water injection network model is calibrated by using the friction factor multiplier.