Reservoir Fluid Volume Control Using 4D Seismic Detectability Maps
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Solution Overview
Problem
Current methods for controlling reservoir fluid volume changes using 4D seismic data face challenges in accurately distinguishing detectability from reservoir models and seismic data, particularly under noise conditions, which affects the reliability of fluid volume change detection and management in hydrocarbon production systems.
Innovation Solution
A computer-implemented method that determines prior and updated fluid volume change detectability probability maps using 4D seismic data, accounting for seismic data noise, and generates control instructions for fluid injection or production systems based on these probabilities, integrating reservoir models and seismic data to propagate uncertainty and improve detection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If 4D seismic data is used to map fluid volume change, then spatial coverage of the reservoir is improved, but measurement precision deteriorates due to seismic data noise
Solution Approach 1:
A probabilistic framework acts as an intermediary between the seismic data and the fluid volume change interpretation. The system introduces probability maps that quantify detectability, serving as a mediator that reconciles the broad spatial coverage of seismic data with the need for precise fluid volume change measurement by filtering out noise-induced uncertainties.
Solution Approach 2:
The system transforms the deterministic interpretation of seismic data into a probabilistic parameter representation. By changing from binary detectable/not-detectable to continuous probability values, the system can better represent the uncertainty introduced by noise while maintaining the spatial coverage benefits of 4D seismic data.
2Reliability
If seismic data noise conditions are accounted for in detectability assessment, then reliability of fluid volume change detection is improved, but device complexity increases
Solution Approach 1:
The detectability assessment is segmented into distinct components: a first probability map assessing detectability without noise considerations, and a second probability map assessing detectability under noise conditions. This segmentation allows the system to systematically account for noise while maintaining a structured, manageable assessment framework rather than a monolithic complex system.
Solution Approach 2:
The system performs preliminary noise characterization and probability map generation before final fluid volume change interpretation. By pre-assessing detectability under various noise conditions and creating probability maps in advance, the system reduces the complexity of real-time decision-making while improving reliability through pre-computed noise adjustments.
3Measurement precision
If prior and updated detectability probability maps are determined, then accuracy of fluid volume change detection is improved, but loss of information increases due to multiple probability estimations
Solution Approach 1:
The system uses feedback by comparing the first detectability probability map (without noise) against the second detectability probability map (with noise). This feedback mechanism allows the system to quantify the impact of noise on detection accuracy and adjust interpretations accordingly, improving overall accuracy while systematically managing the information from multiple probability assessments.
Solution Approach 2:
The final fluid volume change interpretation is created as a composite that integrates information from multiple probability maps. Rather than selecting a single map, the system combines the first and second detectability probability maps into a composite assessment that leverages the strengths of each while mitigating their individual limitations, thereby reducing information loss.
Data Source
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AI summary
Techniques for controlling a hydrocarbon production system include determining a first estimate of a prior FVC detectability probability map based on a plurality of reservoir data that includes four-dimensional (4D) seismic data of a subterranean reservoir; determining a second estimate of the prior FVC detectability probability map under seismic data noise conditions; determining an updated detectable FVC probability based on the 4D seismic data; determining an updated FVC probability based on the updated detectable FVC probability and the first and second estimates of the prior FVC detectability probability maps; and generating a control instruction for at least one of a fluid injection system or a hydrocarbon production assembly based on the updated FVC probability.