Seismic Workflow Resource Provisioning for Plan Deviation Handling
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Solution Overview
Problem
Existing seismic data interpretation methods lack efficiency and accuracy in modeling subsurface structures for resource extraction, leading to inadequate characterization of subsurface regions.
Innovation Solution
A system and method for managing computational resources during seismic workflows by dynamically provisioning additional resources based on deviations from a digital operational plan, utilizing frameworks like PETREL and OCEAN to enhance seismic data processing and simulation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If computational resources are statically allocated for seismic workflows, then resource allocation is simple, but the system cannot adapt to workflow deviations and lacks flexibility
Solution Approach 1:
The patent implements dynamic computational resource allocation by continuously monitoring workflow execution against the digital operational plan and automatically provisioning additional computational resources when deviations are detected. This transforms static resource allocation into a dynamic system that adapts to actual workflow needs in real-time.
Solution Approach 2:
The system establishes a feedback loop where execution information from workflow tasks is compared against the digital operational plan, and based on this comparison, additional computational resources are automatically dispatched. This feedback mechanism enables the system to respond to deviations and maintain optimal performance.
2Reliability
If additional computational resources are provisioned in advance for all possible scenarios, then the system is prepared for any deviation, but resource waste increases
Solution Approach 1:
The system prepares computational resources in advance by having a provisioning mechanism ready to dispatch additional resources when deviations are detected. The digital operational plan is pre-established with expected execution parameters, allowing the system to quickly identify deviations and provision resources only when needed, rather than over-provisioning for all scenarios.
Solution Approach 2:
The system dynamically changes computational resource parameters (such as number of processors, memory allocation, or computational nodes) based on actual workflow execution characteristics. This allows the system to optimize resource usage by adjusting parameters in response to detected deviations rather than maintaining fixed allocations.
3Productivity
If computational resources are dynamically adjusted during workflow execution, then efficiency improves, but system complexity and control difficulty increase
Solution Approach 1:
The system implements self-service by automatically detecting workflow deviations and provisioning additional computational resources without requiring manual intervention. The digital operational plan serves as a self-contained guide that enables the system to autonomously monitor execution, identify deviations, and adjust resources accordingly, reducing the need for complex external control systems.
Data Source
AI summary
A method can include receiving a digital operational plan that specifies computational tasks for seismic workflows, that specifies computational resources and that specifies execution information; dispatching instructions that provision the computational resources for one of the computational tasks for one of the seismic workflows; issuing a request for the execution information; receiving the requested execution information during execution of the one of the computational tasks using the provisioned computational resources; and, based on the received execution information indicating that the execution of the one of the computational tasks deviates from the digital operational plan, dispatching at least one additional instruction that provisions at least one additional computational resource for the one of the computational tasks for the one of the seismic workflows.