Completion Flowrate Design Using Hierarchical Reservoir Streamlines
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Solution Overview
Problem
Computer systems used for modeling hydrocarbon extraction in oilfields face inefficiencies and inaccuracies due to managing large data volumes and timing requirements, leading to delayed or non-optimal design results.
Innovation Solution
A method utilizing a reservoir simulator to obtain a reservoir model state, trace streamlines, detect fluid fronts, group streamlines into hierarchies, determine fluid front time of flights, and assign target flowrates to completion devices to optimize completion design settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional reservoir simulation methods are used to model hydrocarbon extraction, then comprehensive data analysis can be performed, but computational efficiency is reduced and execution time increases
Solution Approach 1:
The reservoir model is segmented into multiple streamline groups organized in a hierarchical structure. Instead of processing the entire reservoir as a single unit, the method divides it into manageable segments (streamline groups at different levels of granularity), allowing parallel processing and reducing computational complexity while maintaining modeling accuracy.
Solution Approach 2:
The method introduces a hierarchical dimension to the streamline organization, creating multiple levels of granularity. This transforms the computational problem from a flat, monolithic structure into a multi-dimensional hierarchy, enabling more efficient computation by processing groups of streamlines at different organizational levels simultaneously.
2Manufacturing precision
If detailed reservoir modeling is performed to ensure accurate completion design, then design quality improves, but execution time increases causing delays
Solution Approach 1:
The method performs preliminary streamline tracing and fluid front detection across the entire reservoir model before detailed completion design. By pre-processing the reservoir model to identify streamline trajectories and fluid front positions, the system prepares essential data in advance, reducing the time required for subsequent completion design calculations while maintaining design quality.
Solution Approach 2:
The completion design process is segmented into distinct phases: streamline tracing, fluid front detection, grouping hierarchy creation, and target flowrate assignment. This segmentation allows each phase to be optimized independently and executed in an efficient sequence, reducing overall execution time while preserving design accuracy.
3Productivity
If comprehensive streamline analysis is conducted to optimize fluid front management, then extraction efficiency improves, but computational resource consumption increases
Solution Approach 1:
Streamlines are segmented into groups organized in a hierarchical structure with multiple levels of granularity. This segmentation allows the system to analyze fluid front behavior at different scales - from individual streamlines to groups of streamlines - enabling efficient resource allocation and fluid front management without requiring exhaustive analysis of every single streamline, thus reducing computational resource consumption.
Solution Approach 2:
The method applies partial action by focusing computational resources on detecting fluid fronts and analyzing critical streamline groups rather than performing exhaustive analysis on all streamlines uniformly. By identifying and prioritizing key fluid front positions and associated streamline groups, the system achieves effective fluid front management with reduced computational resource consumption.
Data Source
AI summary
Using a reservoir simulator, a reservoir model state is obtained. The reservoir model state is used to trace streamlines to obtain streamline trajectories and detect fluid fronts along the streamlines. Using the streamline trajectories, the streamlines are connected to wells. The streamlines are grouped for multiple granularity levels, into groups to obtain a grouping hierarchy. Through the granularity levels of the grouping hierarchy, fluid front time of flights are determined for the groups, and target flowrates assigned to completion devices based on the fluid front time of flights to obtain target flow rates. A completion design is presented that incorporates the target flowrates.