Application of joint seismic traveltime and waveform inversion for near surface velocity modeling on complex land data

2015 ◽  
Author(s):  
Linghe Han ◽  
Ziduo Hu ◽  
Yuchao Wang ◽  
Shujiang Wang
Keyword(s):  
Waveform Inversion ◽  
Surface Velocity ◽  
Near Surface ◽  
Velocity Modeling

Near-surface full-waveform inversion in a transmission surface-consistent scheme

Geophysics ◽  
2020 ◽  
pp. 1-57
Author(s):  
Daniele Colombo ◽  
Ernesto Sandoval ◽  
Diego Rovetta ◽  
Apostolos Kontakis
Keyword(s):  
High Resolution ◽  
Seismic Data ◽  
Waveform Inversion ◽  
Surface Velocity ◽  
Full Waveform Inversion ◽  
Velocity Mapping ◽  
Signal To Noise ◽  
Near Surface ◽  
Velocity Modeling ◽  
Full Waveform

Land seismic velocity modeling is a difficult task largely related to the description of the near surface complexities. Full waveform inversion is the method of choice for achieving high-resolution velocity mapping but its application to land seismic data faces difficulties related to complex physics, unknown and spatially varying source signatures, and low signal-to-noise ratio in the data. Large parameter variations occur in the near surface at various scales causing severe kinematic and dynamic distortions of the recorded wavefield. Some of the parameters can be incorporated in the inversion model while others, due to sub-resolution dimensions or unmodeled physics, need to be corrected through data preconditioning; a topic not well described for land data full waveform inversion applications. We have developed novel algorithms and workflows for surface-consistent data preconditioning utilizing the transmitted portion of the wavefield, signal-to-noise enhancement by generation of CMP-based virtual super shot gathers, and robust 1.5D Laplace-Fourier full waveform inversion. Our surface-consistent scheme solves residual kinematic corrections and amplitude anomalies via scalar compensation or deconvolution of the near surface response. Signal-to-noise enhancement is obtained through the statistical evaluation of volumetric prestack responses at the CMP position, or virtual super (shot) gathers. These are inverted via a novel 1.5D acoustic Laplace-Fourier full waveform inversion scheme using the Helmholtz wave equation and Hankel domain forward modeling. Inversion is performed with nonlinear conjugate gradients. The method is applied to a complex structure-controlled wadi area exhibiting faults, dissolution, collapse, and subsidence where the high resolution FWI velocity modeling helps clarifying the geological interpretation. The developed algorithms and automated workflows provide an effective solution for massive full waveform inversion of land seismic data that can be embedded in typical near surface velocity analysis procedures.

Full waveform inversion: early start of model building process to resolve the complex near surface model in the Exmouth sub-basin, North West Shelf Australia

2018 ◽  
Vol 58 (2) ◽  
pp. 884
Author(s):  
Lianping Zhang ◽  
Haryo Trihutomo ◽  
Yuelian Gong ◽  
Bee Jik Lim ◽  
Alexander Karvelas
Keyword(s):  
Model Building ◽  
Waveform Inversion ◽  
Velocity Model ◽  
Surface Velocity ◽  
Image Point ◽  
Surface Model ◽  
Full Waveform Inversion ◽  
Near Surface ◽  
North West ◽  
Full Waveform

The Schlumberger Multiclient Exmouth 3D survey was acquired over the Exmouth sub-basin, North West Shelf Australia and covers 12 600 km2. One of the primary objectives of this survey was to produce a wide coverage of high quality imaging with advanced processing technology within an agreed turnaround time. The complexity of the overburden was one of the imaging challenges that impacted the structuration and image quality at the reservoir level. Unlike traditional full-waveform inversion (FWI) workflow, here, FWI was introduced early in the workflow in parallel with acquisition and preprocessing to produce a reliable near surface velocity model from a smooth starting model. FWI derived an accurate and detailed near surface model, which subsequently benefitted the common image point (CIP) tomography model updates through to the deeper intervals. The objective was to complete the FWI model update for the overburden concurrently with the demultiple stages hence reflection time CIP tomography could start with a reasonably good velocity model upon completion of the demultiple process.

Introduction to this special section: Near-surface imaging and modeling

2020 ◽  
Vol 39 (5) ◽  
pp. 310-310
Author(s):  
Steve Sloan ◽  
Dan Feigenbaum
Keyword(s):  
Open Source Software ◽  
Special Section ◽  
Waveform Inversion ◽  
Radar Data ◽  
Surface Velocity ◽  
Surface Imaging ◽  
Near Surface ◽  
Velocity Models ◽  
Full Waveform ◽  
Ground Penetrating

This special section on near-surface imaging and modeling was intended originally to focus on improving deeper imaging for exploration purposes through more accurate representations of the near surface, the highly variable zone that energy must traverse through on the way down and back up again to be recorded at the surface. However, as proposed manuscript topics started coming in, it became clear that this section would cover a wider range, from kilometers down to meters. Papers in this section highlight a range of near-surface-related work that includes applying full-waveform inversion (FWI) to improve near-surface velocity models, identifying potential sinkhole hazards before they collapse, the potential of smartphones as geophysical sensors, and new open-source software for ground-penetrating radar data.

Near-surface velocity modeling using a combined inversion of surface and refracted P-waves

2016 ◽  
Vol 35 (11) ◽  
pp. 946-951 ◽  
Author(s):  
Florian Duret ◽  
Frederique Bertin ◽  
Katia Garceran ◽  
Raphael Sternfels ◽  
Thomas Bardainne ◽  
...  
Keyword(s):  
Surface Velocity ◽  
P Waves ◽  
Near Surface ◽  
Velocity Modeling

Land FWI in the Delaware Basin, west Texas: A case study

2020 ◽  
Vol 39 (5) ◽  
pp. 324-331
Author(s):  
Gary Murphy ◽  
Vanessa Brown ◽  
Denes Vigh
Keyword(s):  
Seismic Data ◽  
Waveform Inversion ◽  
Surface Velocity ◽  
High Signal ◽  
Data Sets ◽  
Data Set ◽  
Low Frequencies ◽  
Near Surface ◽  
Delaware Basin ◽  
West Texas

As part of a wide-reaching full-waveform inversion (FWI) research program, FWI is applied to an onshore seismic data set collected in the Delaware Basin, west Texas. FWI is routinely applied on typical marine data sets with high signal-to-noise ratio (S/N), relatively good low-frequency content, and reasonably long offsets. Land seismic data sets, in comparison, present significant challenges for FWI due to low S/N, a dearth of low frequencies, and limited offsets. Recent advancements in FWI overcome limitations due to poor S/N and low frequencies making land FWI feasible to use to update the shallow velocities. The chosen area has contrasting and variable near-surface conditions providing an excellent test data set on which to demonstrate the workflow and its challenges. An acoustic FWI workflow is used to update the near-surface velocity model in order to improve the deeper image and simultaneously help highlight potential shallow drilling hazards.

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