3D Harmonic-Source Reverse Time Migration for Seismic Imaging
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current seismic migration methods, such as reverse time migration (RTM), are computationally expensive and inefficient, particularly when dealing with complex non-horizontal features like steeply dipping reflectors, due to the high computational power required and limitations in handling complex wave velocities.
Innovation Solution
The implementation of a 3D harmonic-source reverse time migration method using a phase-encoding algorithm, which reduces the number of shots needed and eliminates the requirement for sources to be aligned along a straight line, allowing for more efficient processing and cost-effective imaging of subsurface structures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional reverse time migration methods are used to image complex subsurface features, then imaging quality is improved, but computational cost and processing time increase significantly
Solution Approach 1:
The patent segments the seismic data processing into multiple passes or stages, where preliminary processing and filtering are performed before full migration. This divides the computationally intensive task into manageable segments that can be processed more efficiently, reducing overall processing time while maintaining imaging quality.
Solution Approach 2:
The patent employs adaptive parameter selection and optimization, where processing parameters such as wavelet parameters, filtering thresholds, and migration parameters are automatically adjusted based on the specific characteristics of the seismic data. This reduces the need for excessive computational resources by using optimal parameters tailored to each dataset.
2Measurement precision
If conventional reverse time migration methods are used to handle complex wave velocities, then imaging accuracy is improved, but computational resources required increase excessively
Solution Approach 1:
The patent replaces purely computational mechanics with a hybrid approach that incorporates geological knowledge and physical constraints. By using geologically informed initialization and constraint-based optimization, the method reduces the computational burden of handling complex wave velocities while maintaining imaging accuracy.
Solution Approach 2:
The patent uses adaptive parameter optimization where wave velocity models and migration parameters are refined iteratively based on data characteristics. This allows accurate handling of complex wave velocities without requiring excessive computational resources by using optimal parameter sets specific to each geological scenario.
3Adaptability or versatility
If traditional migration methods are used, then processing of steeply dipping reflectors is limited, but the methods remain computationally efficient
Solution Approach 1:
The patent implements dynamic migration approaches where processing parameters and algorithms adapt to the local geological characteristics, including dip angles. This allows the method to handle steeply dipping reflectors effectively by adjusting processing dynamics based on the specific features encountered in the data.
Solution Approach 2:
The patent employs parameter optimization tailored to different geological features, where migration parameters such as angle ranges, wavelet characteristics, and filtering parameters are adjusted based on the dip angles and complexity of the reflectors. This enhances adaptability to steeply dipping structures without excessively increasing method complexity.
Data Source
AI summary
Computing device and method for processing seismic traces to produce an image of a subsurface area. The method includes receiving a series of seismic traces related to the subsurface area and recorded by one or more seismic receivers, wherein the one or more seismic sources are originally generated by a source; applying a phase encoding function to the series of seismic traces, at least a portion of said seismic traces comprise signals reflected by geological interfaces of the subsurface area; applying a 3 dimensional (3D) harmonic-source reverse time migration of the series of seismic traces encoded with the phase encoding function; computing a forward wavefield by solving a first wave equation; computing a backward wavefield by solving a second wave equation; and cross-correlating the forward wavefield with the backward wavefield to generate an image of the subsurface.