Clifford Algebra Seismic Data Decomposition for Reservoir Calibration
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Solution Overview
Problem
Conventional methods for processing multicomponent seismic data are inefficient and struggle to resolve small amplitude signals and noise pulses from low impedance contrast boundaries, limiting the accuracy of subterranean reservoir characterization and calibration of reservoir simulators.
Innovation Solution
The method involves decomposing seismic survey data into a four-dimensional Clifford Algebra form, extracting time delays, and determining time strains from differences in these delays between baseline and monitor surveys, which are then used to calibrate reservoir models by adjusting static model parameters until calculated time strains converge with measured 4D time strains.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional techniques are used for processing multicomponent seismic data, then processing can be performed with standard methods, but the processing is inefficient and requires impracticably large storage and processing capacity
Solution Approach 1:
The patent segments the multicomponent seismic data processing into distinct operational phases: data acquisition, Clifford algebra decomposition, signal extraction, and time strain calculation. This segmentation allows each phase to be optimized independently, reducing overall computational complexity and storage requirements while maintaining processing efficiency
Solution Approach 2:
The patent transforms the seismic data from conventional three-component form into four-dimensional Clifford algebra form, changing the mathematical representation parameters. This parameter transformation enables more efficient signal processing and reduces the computational burden by consolidating multiple signal components into a unified algebraic structure
2Measurement precision
If conventional techniques are used for processing noisy multicomponent seismic data, then standard processing workflows can be applied, but small amplitude signals and noise pulses from low impedance contrast boundaries cannot be resolved
Solution Approach 1:
The patent changes the mathematical parameters of signal representation by decomposing seismic data into Clifford algebra form, which separates signal components more effectively. This parameter transformation enhances the visibility of small amplitude signals from low impedance contrast boundaries by expressing them in a different mathematical basis that better distinguishes signal from noise
Solution Approach 2:
The patent replaces conventional signal processing mechanics with Clifford algebra-based signal extraction. This substitution introduces a more powerful mathematical framework that can resolve overlapping reflected seismic pulses and distinguish small amplitude signals from noise more effectively than traditional mechanical filtering methods
Data Source
AI summary
A system, method, and computer program configured to provide an electronic method for seismic time-lapse characterization of an underground formation are provided. The method includes decomposing, with microprocessor executing a predefined set of instructions stored in a memory, baseline and monitor seismic survey data of a formation into a four dimensional Clifford Algebraic form; extracting, via the microprocessor, time delays from a matrix of decomposed sensor measurement vectors generated based on the four dimensional Clifford Algebra form; and determining, via the processor, time strains for the underground formation from differences in the extracted time delays from the matrix before displaying the determined time strains for the underground formation to a user via a monitor or a hard copy printed document. A procedure is also provided to calibrate and refine the static and dynamic models of an underground formation using the results from the seismic time-lapse characterization.