Seismic First-Arrival Picking via Equivalent Linear Velocity
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional methods for first-arrival picking in seismic data processing are time-consuming and prone to human bias, making them inefficient for large-scale surveys, especially when dealing with noisy data.
Innovation Solution
The method involves using an equivalent linear velocity along a depth dimension to compute first-arrival onsets associated with refracted energy by applying a diving-wave moveout equation and iterating over sub-ranges of offsets, allowing for automated and objective picking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual picking or semi-automatic picking software is used, then first-arrival picking can be performed with human interpretation, but the process becomes time-consuming and reflects subjective biases
Solution Approach 1:
The system performs automated first-arrival picking using computational algorithms that process shot gather data independently without human intervention. The method calculates equivalent linear velocities and picks first arrivals automatically, making the system self-sufficient and eliminating human bias while maintaining high speed processing capability
Solution Approach 2:
The patent replaces the mechanical human interpretation process with an automated computational system. Instead of human operators visually inspecting and picking first arrivals, the system uses diving-wave moveout equations and equivalent linear velocity calculations to automatically determine first-arrival times, substituting mechanical human cognition with algorithmic processing
2Quantity of substance
If conventional picking methods are used on large three-dimensional surveys, then comprehensive coverage is achieved, but the processing becomes extremely time-consuming
Solution Approach 1:
The patent transforms the picking problem by changing parameters from direct time-picking to equivalent linear velocity calculation in the depth dimension. By computing equivalent linear velocities over offset ranges and using iterative sub-range processing, the system achieves rapid processing of large datasets while maintaining accuracy across hundreds of millions of traces
3Measurement precision
If iterative processing over multiple sub-ranges is performed, then accuracy of first arrival onset picking is improved, but computational cost increases
Solution Approach 1:
The patent divides the offset range into multiple sub-ranges and processes each sub-range separately to compute equivalent linear velocities. This segmentation allows the system to achieve high accuracy through iterative refinement while managing computational cost by processing smaller, manageable portions of data in sequence rather than attempting global optimization all at once
Data Source
AI summary
Methods and systems including computer programs encoded on a computer storage medium, for utilizing equivalent linear velocity for first arrival picking of seismic refraction. In one aspect, a method includes receiving data for the shot gather record, generating a diving wave equation curve for a particular parameter pair of multiple parameter pairs, and integrating the shot gather record data corresponding to the diving wave equation curve over a selected range of offsets of the shot gather to generate an equivalent linear velocity value for the particular parameter pair and the shot gather record data, selecting, from the equivalent linear velocity values for the plurality of parameter pairs, a greatest equivalent linear velocity value of the equivalent linear velocity values, the greatest equivalent linear velocity value corresponding to a first-arrival parameter pair, and determining, using the first-arrival parameter pair, a set of first-arrival onsets for the selected sub-range of offsets.