Four-Dimensional Parallel Computing for Electromagnetic Imaging
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Solution Overview
Problem
Current methods for solving Maxwell's equations in 3D for controlled-source electromagnetic surveying in marine environments are computationally intensive and inefficient when using large numbers of processing units, leading to significant challenges in accurately and rapidly inverting resistivity structures for hydrocarbon exploration.
Innovation Solution
A 4D parallelization method is employed, where a large number of processing units are organized into a four-dimensional mesh to solve Maxwell's equations in parallel, allowing for efficient computation by dividing the modeling domain into smaller portions and utilizing sparse communication between processors, enabling simultaneous inversion of multiple data slices and reducing computational inefficiencies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional methods are used to solve Maxwell's equations in 3D, then computational accuracy can be maintained, but computational time and processing efficiency deteriorate significantly
Solution Approach 1:
The patent divides the 3D modeling domain into multiple smaller sub-domains that can be processed independently by different processing units. This segmentation allows parallel computation where each processing unit solves Maxwell's equations for its assigned sub-domain simultaneously, dramatically reducing total computational time while maintaining overall accuracy through proper boundary condition handling at domain interfaces.
Solution Approach 2:
The patent introduces a fourth dimension to the traditional 3D spatial domain by adding a virtual time dimension for iterative solving. This 4D parallelization approach allows multiple iterations of Maxwell's equation solving to proceed simultaneously across different processing units, transforming a sequential time-consuming process into a parallel computation that scales with the number of processing units.
2Productivity
If more processing units are utilized, then computational efficiency improves, but system complexity and communication overhead increase
Solution Approach 1:
The patent segments the computational domain into sub-domains that can be assigned to individual processing units, creating a modular system where each unit operates independently on its assigned portion. This segmentation reduces system complexity by limiting the scope of communication and coordination between processing units, while still achieving high computational efficiency through parallel processing.
Solution Approach 2:
The patent introduces communication interfaces and data exchange mechanisms as intermediaries between processing units. These intermediaries manage the complexity of coordination by providing standardized protocols for data transfer and synchronization, allowing the system to scale efficiently with more processing units without proportionally increasing operational complexity.
3Measurement precision
If iterative numerical methods are used to solve Maxwell's equations, then solution accuracy improves, but computational time increases
Solution Approach 1:
The patent segments the iterative solving process across multiple processing units, where each unit performs iterations on its assigned sub-domain simultaneously. This parallelization maintains the accuracy benefits of iterative methods while reducing total computational time by a factor proportional to the number of processing units, as long as the domain segmentation allows for efficient parallel execution.
Solution Approach 2:
The patent implements continuous iteration and communication between processing units throughout the inversion process. Rather than completing all iterations sequentially, the system maintains continuous useful action by performing iterations concurrently across different domains and communication steps, ensuring that accuracy improvements are achieved without proportional time penalties.
Data Source
AI summary
Method for organizing computer operations on a system of parallel processors to invert electromagnetic field data (11) from a controlled-source electromagnetic survey of a subsurface region to estimate resistivity structure (12) within the subsurface region. Each data processor in a bank of processors simultaneously solves Maxwell's equations (13) for its assigned geometrical subset of the data volume (14). Other computer banks are simultaneously doing the same thing for data associated with a different source frequency, position or orientation, providing a “fourth dimension” parallelism, where the fourth dimension requires minimal data passing (15). In preferred embodiments, a time limit is set after which all processor calculations are terminated, whether or not convergence has been reached.