Field Survey VoI Assessment for Reservoir Surveillance Scheduling
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Solution Overview
Problem
Existing reservoir management and surveillance methods lack an effective way to quantify the value of information (VoI) of field survey services, leading to uninformed decisions and wastage of resources due to schedule-based operations, which can diminish hydrocarbon production.
Innovation Solution
A method and system that utilize scenarios, fluid flow results, and probabilities to quantify the performance of field surveys, employing machine learning techniques to build proxy models for rapid VoI assessment, optimizing surveillance operations based on risk and value analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If field surveys are performed according to a fixed schedule, then surveillance operations are systematically conducted, but resources are wasted and hydrocarbon production is diminished due to lack of value assessment
Solution Approach 1:
The patent transforms the fixed schedule parameter into a dynamic decision-making process by introducing value of information (VoI) assessment. The system calculates VoI metrics based on multiple parameters including production impact, survey cost, and uncertainty reduction, enabling adaptive scheduling that changes parameters based on real-time field conditions and economic considerations.
Solution Approach 2:
The system enables self-service by automatically assessing the value of information for different field survey options without requiring manual economic analysis. The computational framework autonomously evaluates multiple scenarios, compares VoI metrics, and recommends optimal survey decisions, making the system self-sufficient in resource allocation decisions.
2Loss of information
If field surveys are performed frequently to ensure robust surveillance, then data acquisition is maximized, but production is interrupted and resources are expended without guaranteed return
Solution Approach 1:
The patent applies partial action by performing field surveys only to the extent necessary to achieve optimal surveillance value. Rather than conducting surveys on a fixed frequent schedule, the system calculates the precise amount of surveillance data needed based on VoI assessment, performing surveys partially or fully only when the expected information value justifies the production interruption and cost.
Solution Approach 2:
The system transforms static survey scheduling into a dynamic process where survey frequency and timing adapt based on changing field conditions, production rates, and economic parameters. The VoI assessment continuously updates recommendations, making the surveillance strategy flexible and responsive rather than rigid and predetermined.
3Measurement precision
If traditional screening methods using ensembles of geological simulation models are used, then comprehensive uncertainty analysis is performed, but the process is time-consuming and lacks quantitative VoI assessment capability
Solution Approach 1:
The patent creates simplified copy models that replicate the essential uncertainty analysis functionality of comprehensive geological simulation ensembles. These proxy models capture the key relationships and uncertainties but execute much faster, enabling rapid VoI assessment without requiring full ensemble simulations for every decision scenario.
Solution Approach 2:
The system substitutes the mechanical computational process of running numerous full geological simulation ensembles with a streamlined analytical framework. The VoI assessment methodology replaces iterative numerical modeling with direct calculations based on predefined uncertainty parameters and probability distributions, dramatically reducing computation time while maintaining assessment accuracy.
Data Source
AI summary
A method can include receiving scenarios for one or more field sites, where the scenarios account for performance and non-performance of a field survey; generating fluid flow results for each of the scenarios for the one or more field sites; receiving probabilities for at least one technical field survey criterion; and generating values, based on the fluid flow results and the probabilities, that quantify the performance of the field survey at the one or more field sites.