Validating Streamline Simulation with Deep-Look EM Data
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Solution Overview
Problem
The challenge in hydrocarbon reservoir exploitation lies in the uncertainties caused by subsurface heterogeneities, which are not adequately factored into field development plans, leading to increased uncertainties in secondary and tertiary recovery mechanisms.
Innovation Solution
A method for modeling subterranean formations by integrating streamline simulation with deep-look electromagnetic (EM) time-lapse surveys to reduce uncertainty in reservoir models and improve waterflood surveillance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional reservoir modeling methods are used, then the model development is simpler and faster, but the accuracy and reliability of the reservoir model is reduced due to subsurface heterogeneities not being adequately factored in
Solution Approach 1:
The patent combines streamline simulation results with deep-look electromagnetic survey data to create a validated reservoir model. This merging of simulation data with actual field measurements allows the model to account for subsurface heterogeneities while maintaining a systematic modeling approach.
Solution Approach 2:
The patent uses deep-look electromagnetic surveys to obtain actual resistivity measurements from the subsurface, which then serve as feedback to validate and update the streamline simulation model. This feedback loop ensures the model accurately reflects actual subsurface conditions rather than relying solely on theoretical simulations.
2Productivity
If secondary and tertiary recovery mechanisms are implemented, then hydrocarbon recovery is enhanced, but uncertainty in field development increases due to challenges in monitoring these mechanisms
Solution Approach 1:
The patent implements a feedback mechanism where deep-look electromagnetic surveys provide actual subsurface resistivity data that validates the streamline simulation predictions. This allows operators to monitor secondary and tertiary recovery mechanisms with greater confidence, reducing uncertainty in field development while maintaining enhanced recovery productivity.
Solution Approach 2:
The patent replaces traditional mechanical monitoring methods with electromagnetic surveying to track fluid movement and saturation changes in the reservoir. This substitution provides more accurate and comprehensive monitoring of recovery mechanisms, thereby reducing uncertainty while maintaining high productivity.
3Loss of time
If streamline simulation is used without validation, then the modeling process is faster and less resource-intensive, but the reliability of surveillance data is reduced
Solution Approach 1:
The patent replaces unvalidated theoretical modeling with validation against actual electromagnetic survey data. This substitution ensures surveillance reliability while maintaining the efficiency of streamline simulation by using it as the base model that is then validated rather than replacing it entirely with more time-consuming methods.
Solution Approach 2:
The patent uses electromagnetic survey results as feedback to validate streamline simulation predictions. This feedback approach maintains the speed advantage of streamline simulation while ensuring reliability by confirming predictions against actual field measurements.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances the accuracy of waterflood surveillance by validating streamlines with deep-look EM data, thereby reducing uncertainty and improving field development planning, including enhanced oil recovery (EOR) strategies.
Implementation Method 1
deep-look electromagnetic (EM) time-lapse surveys
Data Source
Figure 1A~1D
Figure 2
Figure 3A
AI summary
A method for modeling a subterranean formation includes measuring or receiving cross-well electromagnetic data representing a subterranean formation. The method also includes producing a resistivity profile of the subterranean formation based at least partially upon the cross-well electromagnetic data. The method also includes determining a static model of the subterranean formation based at least partially upon the resistivity profile. The method also includes determining a dynamic model of the subterranean formation based at least partially upon the static model.