3D Quality Factor Model from Vertical Seismic Profiles
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Solution Overview
Problem
Current seismic modeling techniques face challenges in accurately compensating for energy loss in vertical seismic profile (VSP) data, leading to poor resolution and uncertainty in subterranean formation imaging and hydrocarbon reservoir characterization.
Innovation Solution
A three-dimensional quality factor model is developed using the spectral ratio method from zero offset VSPs, with geostatistical kriging to interpolate quality factors across a volume, enhancing surface seismic data compensation and amplitude versus offset analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional seismic modeling techniques are used to map subterranean formations, then structural maps can be produced to identify impermeable layers and faults, but energy loss in VSP data leads to poor resolution and uncertainty in formation imaging
Solution Approach 1:
The patent converts the harmful effect of energy loss in VSP data into a beneficial tool by calculating the quality factor (Q) from the observed amplitude and frequency attenuation. This Q factor is then used to compensate the surface seismic data, transforming the previously harmful energy loss into useful information for improving imaging resolution and AVO analysis.
Solution Approach 2:
The patent changes the parameter representation by introducing time and depth variant quality factors derived from spectral ratios of VSP data. These varying Q parameters are used to compensate surface seismic data, improving the resolution and accuracy of subterranean formation imaging beyond what conventional constant-parameter methods can achieve.
2Reliability
If VSP data is used directly for surface seismic compensation, then amplitude and frequency information can be obtained, but near-surface data quality issues and frequency loss limit the effectiveness
Solution Approach 1:
The patent extracts the quality factor information from VSP data through spectral ratio analysis, separating the useful attenuation characteristics from the problematic near-surface noise and frequency loss. By extracting only the essential Q parameter information and applying it to compensate surface seismic data, the method eliminates the harmful effects of poor near-surface data quality while retaining the beneficial amplitude and frequency correction capabilities.
3Measurement precision
If quality factors are estimated from VSP data using spectral ratio method, then time and depth variant Q factors can be obtained, but interpolation between wells using geostatistical kriging adds computational complexity
Solution Approach 1:
The patent introduces geostatistical kriging as an intermediary method to bridge the gap between discrete well-based Q factor measurements and continuous three-dimensional formation modeling. This statistical interpolation technique serves as a mediator that systematically estimates Q values throughout the subsurface volume, balancing measurement accuracy with computational feasibility by providing a structured approach to spatial extrapolation.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach provides higher resolution images, improved acoustic impedance inversion, and reduced uncertainty in depth estimation, overcoming limitations of near-surface data quality and frequency loss in existing VSP surveys.
Implementation Method 1
the quality factor is estimated using the spectral ratio method from zero offset VSPs
Implementation Method 2
the quality factor quantifies the energy loss of a propagating wavelet with time due to fluid movement and friction with grain boundary
Implementation Method 3
These quality factors are populated on the surface seismic in between the wells using geostatistical kriging
Implementation Method 4
Seismic body waves travel into the ground, are reflected by subsurface formations, and return to the surface where they recorded by sensors called geophones
Implementation Method 5
for each of the vertical seismic profiles, injecting a ground force into the vertical seismic profile to provide a reference trace at depth zero in order to estimate energy loss in each receiver
Data Source
AI summary
Systems and methods develop a three-dimensional model of a subterranean formation based on vertical seismic profiles at a plurality of well locations. This approach can include receiving seismic data for the subterranean formation including the vertical seismic profiles; for each vertical seismic profile, injecting a ground force into the vertical seismic profile to provide a reference trace at depth zero to estimate energy loss in each receiver providing data in the vertical seismic profile and estimating time and depth variant quality factors for the well location associated with the vertical seismic profile based on the seismic profile; estimating quality factors for points within a three-dimensional volume representing the subterranean formation by interpolating between the time and depth variant quality factors for the location associated with each vertical seismic profile; and combining estimated quality factors to generate a three-dimensional quality factor model of the three-dimensional volume representing the subterranean formation.