Well Cluster Production Optimization via Computational Estimation
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Solution Overview
Problem
Current hydrocarbon production systems face challenges in accurately tracking individual well productions in real time due to commingled fluid streams, limited capacity in manifolds and separators, and the high cost and complexity of multiphase flowmeters, leading to inefficient well management and optimization.
Innovation Solution
A method called Production Universe Real Time Optimization (PU RTO) that involves well testing, estimation modeling, dynamic fluid flow monitoring, and reconciliation processes to estimate individual well contributions, allowing for real-time optimization of well production without the need for multiphase meters, using flow meters and interaction pressure data to adjust production variables and achieve optimization targets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiphase flowmeters are installed on individual well flowlines to measure oil, water and gas components continuously, then measurement precision is improved, but device complexity and cost increase significantly
Solution Approach 1:
The patent introduces an intermediary computational model that acts as a mediator between the commingled separator measurements and individual well production estimates. Instead of directly measuring each well's multiphase flow, the system uses a mathematical model (mass balance equations) to compute individual well contributions from the commingled stream measurements, thereby avoiding the need for complex multiphase meters at each wellhead.
Solution Approach 2:
The patent replaces the mechanical measurement system (multiphase flowmeters) with a computational/mathematical system. The core mechanism is a set of mass balance equations that computationally allocate the commingled separator measurements to individual wells based on well-specific parameters and production characteristics, substituting physical measurement devices with mathematical modeling.
2Measurement precision
If multiphase flowmeters are used to measure individual well production, then measurement precision is improved, but cost increases significantly
Solution Approach 1:
The patent employs inexpensive flow meters installed only at the separator outlets to measure total commingled production of oil, water, and gas. These simple, low-cost measurements are then used as inputs to the computational model to derive individual well production estimates, replacing the expensive multiphase meters that would be needed at each well.
Solution Approach 2:
The computational mass balance model serves as an intermediary that transforms the cheap separator-level measurements into accurate well-level production estimates, bridging the gap between low-cost bulk measurements and high-value individual well information without requiring expensive wellhead instrumentation.
3Ease of operation
If commingled fluid streams are used from multiple wells, then ease of operation is improved, but measurement precision of individual well production deteriorates
Solution Approach 1:
The system implements a feedback mechanism where the computational model continuously estimates individual well production based on commingled separator measurements and well-specific parameters. This feedback loop allows operators to monitor and adjust individual well performance while maintaining the operational simplicity of commingled flow management, effectively decoupling the operational simplicity from the ability to track individual well metrics.
4Device complexity
If the capacity of manifolds and separators is limited, then device complexity is reduced, but productivity of the well cluster deteriorates
Solution Approach 1:
The patent applies partial action by implementing individual well production optimization only for wells that are bottlenecks or underperforming, rather than attempting to optimize the entire well cluster simultaneously. The computational model identifies specific wells where production adjustments would yield the greatest benefit, allowing targeted interventions that improve overall productivity without requiring complete system redesign.
Data Source
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AI summary
The present invention relates to a method to optimise production of a cluster of wells on the basis of an estimation of the contributions of individual wells to the production of the cluster of wells, tailored to the particular constraints and requirements of the oil and gas production environment. The wells in the cluster may differ in terms of nature and flux of its effluents, and/or mode of operation, stimulation and/or manipulation. The wells may also produce from multiple subsurface zones or branches. The wellheads of the wells in the cluster may be located on land or offshore, above the surface of the sea or on the seabed. The method according to the invention may be used to generate one or more optimisation models, taking into account only significantly relevant well and production syatem characeristics and effects.