Surface seismics with DAS: An emerging alternative to modern point-sensor acquisition

2020 ◽  
Vol 39 (11) ◽  
pp. 808-818
Author(s):  
Andrey Bakulin ◽  
Ilya Silvestrov ◽  
Roman Pevzner
Keyword(s):  
Data Quality ◽  
Surface Characterization ◽  
Waveform Inversion ◽  
Velocity Model ◽  
Desert Environment ◽  
Near Surface ◽  
Distributed Sensors ◽  
Borehole Geophysics ◽  
Vertical Arrays ◽  
Simultaneous Acquisition

Land seismic acquisition is moving toward “light and dense” geometries, with point receiver systems believed to be an ultimate configuration of choice. Cableless land nodal systems enable more flexible spatial sampling at the price of eliminating even small arrays. For large surveys in a desert environment, such spacing remains insufficient to address the complex near surface, while recordings with single sensors exhibit a significant reduction in data quality. At the same time, exploration problems increasingly demand smaller uncertainty in all seismic products. While 1 m geophone sampling could have addressed these problems, it remains out of economic reach as point sensor cost plateaus. We examine an emerging alternative technology of distributed acoustic sensing (DAS) that revolutionized borehole geophysics but is still mostly unknown in the seismic world. Fully broadband DAS sensors promise massive channel count and uncompromised inline sampling down to 0.25 m. Their distributed nature offers the unique capability to conduct a continuous recording with multiscale grids of “shallow,” “deep,” and “full-waveform inversion” receivers, all implemented with a single set of fixed cables and only one round of shooting. These distinct features allow us to simultaneously pursue near-surface characterization, imaging of deeper targets, and velocity model evaluation. Specifically, in a desert environment, distributed sensors may offer superior data quality compared to point sensors, whereas DAS capability of “seismic zoom” in the near surface becomes instrumental for near-surface characterization. Finally, simultaneous acquisition of surface seismic and vertical arrays that can be achieved easily with DAS can effectively address the exploration of subtler targets such as low-relief structures. We support these findings with a field case study from a desert environment and synthetic examples. With many distinct advantages, surface seismic with DAS emerges as a compelling alternative to modern point-sensor acquisitions.

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.

Random objective waveform inversion of surface waves

Geophysics ◽  
2020 ◽  
Vol 85 (4) ◽  
pp. EN49-EN61
Author(s):  
Yudi Pan ◽  
Lingli Gao
Keyword(s):  
Objective Function ◽  
Surface Waves ◽  
Waveform Inversion ◽  
Velocity Model ◽  
Initial Model ◽  
S Wave ◽  
Data Set ◽  
Near Surface ◽  
Synthetic Test ◽  
Ground Penetrating

Full-waveform inversion (FWI) of surface waves is becoming increasingly popular among shallow-seismic methods. Due to a huge amount of data and the high nonlinearity of the objective function, FWI usually requires heavy computational costs and may converge toward a local minimum. To mitigate these problems, we have reformulated FWI under a multiobjective framework and adopted a random objective waveform inversion (ROWI) method for surface-wave characterization. Three different measure functions were used, whereas the combination of one measure function with one shot independently provided one of the [Formula: see text] objective functions ([Formula: see text] is the total number of shots). We have randomly chose and optimized one objective function at each iteration. We performed a synthetic test to compare the performance of the ROWI and conventional FWI approaches, which showed that the convergence of ROWI is faster and more robust compared with conventional FWI approaches. We also applied ROWI to a field data set acquired in Rheinstetten, Germany. ROWI successfully reconstructed the main geologic feature, a refilled trench, in the final result. The comparison between the ROWI result and a migrated ground-penetrating radar profile further proved the effectiveness of ROWI in reconstructing the near-surface S-wave velocity model. We also ran the same field example by using a poor initial model. In this case, conventional FWI failed whereas ROWI still reconstructed the subsurface model to a fairly good level, which highlighted the relatively low dependency of ROWI on the initial model.

1D Laplace-Fourier Acoustic FWI for Near-Surface Characterization and Initial Velocity Model Building

2020 ◽  
Author(s):  
A. Kontakis ◽  
D. Rovetta ◽  
D. Colombo ◽  
E. Sandoval-Curiel ◽  
P.V. Petrov ◽  
...  
Keyword(s):  
Initial Velocity ◽  
Surface Characterization ◽  
Model Building ◽  
Velocity Model ◽  
Near Surface ◽  
Velocity Model Building

Revitalizing seismic data with new imaging solutions to positively impact field development

2019 ◽  
Vol 38 (1) ◽  
pp. 20-26
Author(s):  
Gareth Venfield ◽  
Michael Townsend ◽  
Paul Cattermole ◽  
Tony Martin ◽  
Stuart Fairhead
Keyword(s):  
Seismic Data ◽  
Model Building ◽  
Large Population ◽  
Waveform Inversion ◽  
Structural Complexity ◽  
Velocity Model ◽  
Near Surface ◽  
Field Development ◽  
The North ◽  
The Right

Evaluating, planning, and forecasting are integral parts of asset development and continue throughout the life cycle of a producing field. The right decisions are required to lower risk and maximize economic recovery in challenging environments. The Claymore Complex is located in the North Sea and was discovered in 1977. A number of geologic challenges affect the imaging and hence field development including a system of shallow interweaving Quaternary channels, numerous high-contrast layers of varying composition, overburden structural complexity, and a sequence of tilted fault blocks containing the main reservoir systems. Historically, seismic processing over the area has not fully solved these challenges, resulting in significant imaging uncertainty. The Claymore Complex has an abundance of data including a large population of well information and interpretation. As part of a data revitalization process, geostatistical integration of these auxiliary data into a velocity model building sequence using full-waveform inversion and wavelet shift tomography enabled the generation of an accurate high-resolution velocity model. Access to a recent 3D survey acquired obliquely to existing data improved subsurface illumination for both the model building and imaging phases. Near-surface imaging effects and their impact on reservoir positioning and clarity were improved using the upgraded velocity model and dual-azimuth data. Shallow imaging challenges were mitigated by utilizing the additional illumination and angular diversity contained within the multiple reverberations. The revitalization of the Claymore area seismic data has challenged the current understanding of the geologic framework. Confidence has been improved by solving depth conversion problems and increasing the understanding of fault positioning and reservoir connectivity, which are invaluable for future field development.

Fast 2D full-waveform modeling and inversion using the Schur complement approach

Geophysics ◽  
2019 ◽  
Vol 84 (5) ◽  
pp. R783-R792 ◽  
Author(s):  
Debanjan Datta ◽  
Piyoosh Jaysaval ◽  
Mrinal Sen ◽  
Adrien F. Arnulf
Keyword(s):  
Water Column ◽  
Linear Equations ◽  
Waveform Inversion ◽  
Schur Complement ◽  
Simple Algebra ◽  
Velocity Model ◽  
Near Surface ◽  
Full Waveform ◽  
Anomalous Zone ◽  
And Inversion

In most full-waveform inversion (FWI) problems, sufficient prior information is available to constrain the velocity of certain parts of the model, e.g., the water column or, in some cases, near-surface velocities. We take advantage of this situation and develop a fast Schur-complement-based forward modeling and inversion approach by partitioning the velocity model into two parts. The first part consists of the constrained zone that does not change during the inversion, whereas the second part is the anomalous zone to be updated during the inversion. For this decomposition, we partially factorize the governing system of linear equations by computing a Schur complement for the anomalous zone. The Schur complement system is then solved to compute the fields in the anomalous zone, which are then back substituted to compute the fields in the constrained region. For each successive modeling steps with new anomalous zone velocities, the corresponding Schur complement is easily computed using simple algebra. Because the anomalous part of the model is comparatively smaller than the whole model, considerable computational savings can be achieved using our Schur approach. Additionally, we showed that the Schur complement method maintains the accuracy of standard frequency-domain finite difference formulations, but this comes at a slightly higher peak memory requirement. Our FWI workflow shows reduced runtime by 15%–57% depending upon the depth of the water column without losing any accuracy compared to the standard method.

Near-surface characterization using traveltime and full-waveform inversion with vertical and horizontal component seismic data

2019 ◽  
Vol 7 (1) ◽  
pp. T141-T154 ◽  
Author(s):  
Md. Iftekhar Alam
Keyword(s):  
Surface Characterization ◽  
Seismic Waves ◽  
Seismic Velocity ◽  
Waveform Inversion ◽  
Horizontal Component ◽  
Full Waveform Inversion ◽  
Near Surface ◽  
Velocity Modeling ◽  
Full Waveform ◽  
Attenuation Models

Seismic imaging of the shallow subsurface (approximately 5 m) can be very challenging when reflections are absent and the data are dominated by ground roll. I analyzed the transmission coda to produce fine-scale, interpretable vertical and horizontal component seismic velocity ([Formula: see text] and [Formula: see text]) models using full-waveform inversion (FWI). Application of FWI is tested through imaging two buried targets. The first target is a pair of well-documented utility pipes with known diameters (0.8 m) and burial depths (approximately 1.5 m). The second target is a poorly documented former location of the pipe(s), which is now a backfilled void. Data are acquired along a 23 m 2D profile using a static array with single-component vertical and horizontal geophones. Our results indicate considerable velocity updates in the [Formula: see text] and [Formula: see text] models across the pipes and backfill. The pipes appear as negative velocity updates in the final inverted [Formula: see text] and [Formula: see text] models, whereas the backfilled area represents negative and positive velocity updates in the [Formula: see text] and [Formula: see text] models, respectively. Variations of the polarities in the inverted models ([Formula: see text] and [Formula: see text]) across the backfill can be indicative of the medium, which respond differently to the vertical and horizontal component seismic waves. The attenuation models show a general decreasing trend with increasing depth. Therefore, simultaneous applications of vertical ([Formula: see text]) and horizontal ([Formula: see text]) component seismic velocity modeling can be an effective tool to understand the subsurface medium in near-surface characterization.

Near-surface velocity estimation using source-domain full traveltime inversion and early arrival waveform inversion

Geophysics ◽  
2018 ◽  
Vol 83 (4) ◽  
pp. R335-R344 ◽  
Author(s):  
Lu Liu ◽  
Yan Wu ◽  
Bowen Guo ◽  
Song Han ◽  
Yi Luo
Keyword(s):  
Plane Wave ◽  
Waveform Inversion ◽  
Velocity Model ◽  
Velocity Estimation ◽  
Surface Velocity ◽  
Accurate Estimation ◽  
Near Surface ◽  
Traveltime Inversion ◽  
Source Domain ◽  
Early Arrival

Accurate estimation of near-surface velocity is a key step for imaging deeper targets. We have developed a new workflow to invert complex early arrivals in land seismic data for near-surface velocities. This workflow is composed of two methods: source-domain full traveltime inversion (FTI) and early arrival waveform inversion (EWI). Source-domain FTI automatically generates the background velocity that kinematically matches the reconstructed plane-wave sources from early arrivals with true plane-wave sources. This method does not require picking first arrivals for inversion, which is one of the most challenging and labor-intensive steps in ray-based first-arrival traveltime tomography, especially when the subsurface medium contains low-velocity zones that cause shingled multivalue arrivals. Moreover, unlike the conventional Born-based method, source-domain FTI can determine if the initial velocity is slower or faster than the true one according to the gradient sign. In addition, the computational cost is reduced considerably by using the one-way wave equation to extrapolate the plane-wave Green’s function. The source-domain FTI tomogram is then used as the starting model for EWI to obtain the short-wavelength component associated with the velocity model. We tested the workflow on two synthetic and one onshore filed data sets. The results demonstrate that source-domain FTI generates reasonable background velocities for EWI even though the first arrivals are shingled, and that this workflow can produce a high-resolution near-surface velocity model.

An application of full-waveform inversion to land data using the pseudo-Hessian matrix

2016 ◽  
Vol 4 (4) ◽  
pp. T627-T635
Author(s):  
Yikang Zheng ◽  
Wei Zhang ◽  
Yibo Wang ◽  
Qingfeng Xue ◽  
Xu Chang
Keyword(s):  
Hessian Matrix ◽  
Waveform Inversion ◽  
Computational Cost ◽  
Velocity Model ◽  
Surface Velocity ◽  
Full Waveform Inversion ◽  
Data Set ◽  
Near Surface ◽  
Full Waveform ◽  
The Time Domain

Full-waveform inversion (FWI) is used to estimate the near-surface velocity field by minimizing the difference between synthetic and observed data iteratively. We apply this method to a data set collected on land. A multiscale strategy is used to overcome the local minima problem and the cycle-skipping phenomenon. Another obstacle in this application is the slow convergence rate. The inverse Hessian can enhance the poorly blurred gradient in FWI, but obtaining the full Hessian matrix needs intensive computation cost; thus, we have developed an efficient method aimed at the pseudo-Hessian in the time domain. The gradient in our FWI workflow is preconditioned with the obtained pseudo-Hessian and a synthetic example verifies its effectiveness in reducing computational cost. We then apply the workflow on the land data set, and the inverted velocity model is better resolved compared with traveltime tomography. The image and angle gathers we get from the inversion result indicate more detailed information of subsurface structures, which will contribute to the subsequent seismic interpretation.

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