Back Allocation of Commingled Zone Flow Rates
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Solution Overview
Problem
Current methods for determining individual well flow rates in commingled zones are inaccurate and costly, as they often require shutting in wells for measurement, fail to account for changes in production ratios, and do not reconcile with cumulative production, leading to inconsistent and delayed reporting.
Innovation Solution
A computer-implemented method that calculates predicted flow rates for individual zones by comparing them to measured rates and adjusting to reconcile cumulative production, using a combination of models such as pressure transient analysis, material balance, and history-matching, with iterative processes to ensure accuracy and account for fluid transients and changes in well production.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current methods (shut-in measurements, test separators) are used to determine individual well flow rates, then measurement precision is improved, but productivity is worsened due to well shut-ins and production delays
Solution Approach 1:
The patent replaces mechanical measurement systems (shut-in measurements, test separators) with a computational model-based system that uses pressure transient analysis, material balance equations, and history-matching to calculate individual zone flow rates continuously without physical intervention, thereby maintaining productivity while achieving measurement precision
Solution Approach 2:
The patent introduces an intermediary computational model that acts as a mediator between available data (pressure measurements, cumulative production) and the desired output (individual zone flow rates), allowing indirect determination of flow rates without direct measurement that would require shut-ins
2Measurement precision
If rate allocation methods are used to calculate allocation factors based on periodic separator tests, then measurement precision is improved, but loss of time is worsened due to delayed production reporting
Solution Approach 1:
The patent performs preliminary action by continuously running the computational model in the background using available data, so that when production allocation is needed, the results are immediately available without waiting for periodic separator tests, thereby reducing reporting delay while maintaining accuracy
Solution Approach 2:
The patent implements continuous action by constantly updating the computational model with incoming pressure and production data, ensuring that allocation factors are continuously refined and available in real-time, eliminating the discontinuous nature of periodic testing and reporting
3Device complexity
If constant allocation factors are applied to commingled zones, then device complexity is reduced, but reliability is worsened due to inconsistency with downhole pressure changes
Solution Approach 1:
The patent applies dynamics by making allocation factors dynamic rather than constant, allowing them to change in response to updated pressure measurements and production data through iterative model adjustment, thereby maintaining consistency with downhole pressure changes while adding only moderate computational complexity
Data Source
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AI summary
Methods and system for incorporating downhole and surface data with models and adjustment algorithms to back allocate flow rates of commingled zones. The models include fluid flow in the reservoir and wellbore, pressure drop across a choke, and fluid flow in the well completion. The models are coupled with an algorithm for comparing the results from the individual commingled zones to the total cumulative commingled volume and adjusting at least one predicted rate so that they match the measured flow rate over a specified time period. One method utilizes a reassignment factor for the adjustment of the predicted rates. These comparisons and allocation adjustments can be accomplished even when the frequency of the commingled flow rate and cumulative measurements, and the frequency of the predicted rates from the model differ from each other and the specified time period.