Andrey Bakulin
UT Austin, Bureau of Economic Geology, Department Member
- Saudi ARAMCO, EXPEC Advanced Research Center, Department Memberadd
- Andrey Bakulin gained a Ph.D. in Geophysics from St. Petersburg State University of Russia. While in academia, he con... moreAndrey Bakulin gained a Ph.D. in Geophysics from St. Petersburg State University of Russia. While in academia, he contributed to setting foundations for quantitative seismic fracture characterization using seismic anisotropy with the key Geophysics paper “Estimation of fracture parameters from reflection seismic data” cited more than 700 times. Andrey joined the industry in 1999 and worked at Schlumberger Cambridge Research, Shell Bellaire Technology Center, and WesternGeco. He co-developed the Virtual Source Method as the first industrial application of seismic interferometry. He deployed practical methods for estimating anisotropy from seismic and designed rock physics transforms to characterize fractures and 3D stresses from seismic anisotropy. He pioneered localized tomography with borehole data remains the primary method of deriving anisotropic parameters for velocity model building. Since 2010 he has worked at Saudi Aramco’s EXPEC Advanced Research Center in Dhahran. Currently, he leads the focus area for Data Acquisition and Robotization. His most recent achievements include solving near-surface scattering noise challenges, making 3D seismic survey design transparent to intrepreters, successful permanent seismic monitoring of land carbonates with buried receivers, and development of seismic and uphole acquisition with Distributed Acoustic Sensing. He served SEG in various roles, including the 2011 Spring Distinguished Lecturer on a Virtual Source. He is frequently recognized as a top presenter at SEG and won two Best Paper at SEG awards. He has numerous professional awards, with the latest including the 2019 Conrad Schlumberger Medal from EAGE for “solving problems that impact data quality and efficiency”.edit
We simulate a fault/fracture zone in a physical modeling experiment as array of thin, air‐filled, densely packed rectangular cracks that have different sizes and shapes. For a fixed surface area of the fault occupied by cracks and for a... more
We simulate a fault/fracture zone in a physical modeling experiment as array of thin, air‐filled, densely packed rectangular cracks that have different sizes and shapes. For a fixed surface area of the fault occupied by cracks and for a constant fracture porosity, we ...
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P097 Tube-Wave Reflections in Cased Boreholes D. Alexandrov (St.-Petersburg State University) B.M. Kashtan (St.- Petersburg State University) A.V. Bakulin (Shell International Exploration and Production Inc) & S.R. Ziatdinov*... more
P097 Tube-Wave Reflections in Cased Boreholes D. Alexandrov (St.-Petersburg State University) B.M. Kashtan (St.- Petersburg State University) A.V. Bakulin (Shell International Exploration and Production Inc) & S.R. Ziatdinov* (St.-Petersburg State University) SUMMARY At low frequencies tube or Stoneley waves represent a dominant arrival propagating along boreholes. They can be excited by the source in a well or by external source due to conversion from other wave types. Tube wave experiences reflection at the bed boundaries borehole diameter changes and fractures or permeable zones. It was proven in previous studies that 1D effective wavenumber approach provides simple and accurate low-frequency description
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© 2018 SEG. Unlike conventional point sensors, Distributed Acoustic Sensing (DAS) has unique features allowing us to record multiple datasets with variable acquisition parameters set inside the recording box, while using one continuous... more
© 2018 SEG. Unlike conventional point sensors, Distributed Acoustic Sensing (DAS) has unique features allowing us to record multiple datasets with variable acquisition parameters set inside the recording box, while using one continuous recording cable and a single round of shooting. We reveal how these distinct features allow DAS to deliver multi-scale data and have the capability to focus on both the near surface and deeper targets simultaneously. We present synthetic and field examples of “deep” and “shallow” DAS surveys and demonstrate their effectiveness. The new capabilities of surface seismic with DAS technology comprise a sensing revolution that addresses long-standing near-surface issues in land seismic without compromising the deeper imaging
Research Interests: Geology and Seismology
Research Interests: Geology and Seismology
Research Interests: Geology and Seismology
In 2015, Saudi Aramco started a CO2 Water-Alternating-Gas (WAG) EOR pilot project in an onshore carbonate reservoir. To monitor lateral expansion of the CO2 plume, the area was instrumented with a hybrid surface/downhole permanent seismic... more
In 2015, Saudi Aramco started a CO2 Water-Alternating-Gas (WAG) EOR pilot project in an onshore carbonate reservoir. To monitor lateral expansion of the CO2 plume, the area was instrumented with a hybrid surface/downhole permanent seismic monitoring system. This system consists of over 1000 buried seismic sensors at a depth of around 70 m, below the the depth of expected weathering layer to mitigate the time-lapse noise. Despite receiver burial, seismic data still suffers from numerous challenges including: significant amounts of high-amplitude coherent noise such as guided waves, mode conversions, and scattered energy; amplitude variations over space and time caused by source and receiver coupling; variability of wavelet shape and arrival times due to seasonal near-surface variations; and low signal-to-noise ratio (SNR). A novel processing workflow was designed for 4D processing of such data. The workflow involves five critical processes. First, the high-amplitude coherent noise is eliminated using FK-based techniques that are 4D compliant to preserve the reservoir changes between repeated seismic surveys. Second, a four-term joint surface-consistent amplitude-scaling algorithm resolves the amplitude variations. The algorithm allows both source and receiver terms to have different scalars for the same positions, but it restricts the other two terms to be position-invariant over different time-lapse surveys, as the window of analysis does not include the reservoir. This is to guarantee that the source and receiver terms are survey-dependent while the other two terms are survey-independent. Thus, the amplitude variability is linked to source and receiver positions over space and time. It also assures that the reservoir changes are not affected by changes in the overburden. Third, wavelet shape variations are addressed using a four-term joint surface-consistent spiking deconvolution algorithm that applies similar principle as the scaling algorithm. Fourth, the small variations in reflection times between different surveys (4D statics) caused by seasonal variations are corrected by a specialized surface-consistent residual statics algorithm using a common pilot derived from the base survey. Fifth, the pre-stack data is supergrouped to enhance the signal-to-noise ratio and repeatability. The processing workflow has been applied to frequent land 3D seismic data acquired over a CO2 WAG EOR pilot project in Saudi Arabia. As a result, we obtained very repeatable seismic images that may successfully detect small CO2-related changes in a stiff carbonate reservoir.
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We thank Jan Walda from the University of Hamburg, mem-bers of the Seismic Modeling and Inversion group (SMI) andthe Seismic Wave Analysis Group (SWAG) at KAUST for con-structive discussions. The research reported in this publica-tion was... more
We thank Jan Walda from the University of Hamburg, mem-bers of the Seismic Modeling and Inversion group (SMI) andthe Seismic Wave Analysis Group (SWAG) at KAUST for con-structive discussions. The research reported in this publica-tion was supported by funding from King Abdullah Universityof Science and Technology (KAUST), Thuwal, 23955-6900,Saudi Arabia and Saudi Aramco.
Research Interests: Geology and Seismology
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A novel integrated land seismic imaging system that uses distributed acoustic sensing (DAS) in a grid of shallow upholes is proposed. This system allows simultaneous land near-surface characterization and subsurface imaging in a... more
A novel integrated land seismic imaging system that uses distributed acoustic sensing (DAS) in a grid of shallow upholes is proposed. This system allows simultaneous land near-surface characterization and subsurface imaging in a cost-efficient manner. Using this fiber-optic system, uphole velocity surveys can be acquired at any time with a single shot, since all depth levels are recorded simultaneously. Dense grids of smart DAS upholes accurately characterize long-wavelength statics and reduce uncertainty in exploration for low-relief structures. In addition, connecting multiple upholes with a single fiber enables efficient acquisition of seismic surveys with buried vertical arrays, which can provide superior images of the deeper subsurface than surface seismic, but with improved accuracy, since they bypass most of the near-surface complexities. The smart DAS upholes can deliver on-demand surveys that simultaneously characterize the near surface and perform deep reflection imaging o...
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We have developed a fast direct solver for numerical simulation of acoustic waves in 3D heterogeneous media. The Helmholtz equation is approximated by a 27-point finite-difference stencil of second-order accuracy that is optimized to... more
We have developed a fast direct solver for numerical simulation of acoustic waves in 3D heterogeneous media. The Helmholtz equation is approximated by a 27-point finite-difference stencil of second-order accuracy that is optimized to reduce the numerical dispersion. Due to the optimization, dispersion errors less than 1% are achieved with model discretization of only five points per wavelength. Wave-propagation problem requires solving a large system of linear equations with complex sparse symmetric coefficient matrix with seismic shots representing the right-hand side. The first step is the triangular factorization of the coefficient matrix followed by solving systems of linear equations with triangular coefficient matrices as a second step. Having defined the triangular factors, the second step is very cheap, and its linear scaling with respect to the number of shots is the main advantage of direct methods. To reduce memory consumption and computational time at the factorization s...
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In 2015, Saudi Aramco commenced its first carbon capture and sequestration project, with carbon dioxide (CO2) injected into a small area of a carbonate reservoir located in the Eastern Province of Saudi Arabia. To monitor the expansion of... more
In 2015, Saudi Aramco commenced its first carbon capture and sequestration project, with carbon dioxide (CO2) injected into a small area of a carbonate reservoir located in the Eastern Province of Saudi Arabia. To monitor the expansion of the CO2 plume, continuous 4D seismic data is being recorded at an average rate of one survey per month. The interpretability of data requires: (1) a high degree of repeatability, which has been achieved through dedicated acquisition and processing, (2) sufficient sensitivity of seismic data to injected CO2, (3) accurate characterization of reservoir heterogeneity, and (4) a fit-for-purpose workflow to interpret time-lapse seismic images. This paper focuses on the last three points. First, a rock physics model (RPM) is calibrated from available well data (well logs, fluid analysis), showing that CO2 injection causes a drop in both acoustic impedance and Poisson's ratio of 6% at the well log scale, leading to moderate seismic data sensitivity, an...
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Research Interests: Geology and Overburden
Seismic speckle noise is the primary factor causing severe reflection distortions caused by small-scale near-surface scattering. As in the case of speckle noise in optics and acoustics, deterministic velocity model-building techniques... more
Seismic speckle noise is the primary factor causing severe reflection distortions caused by small-scale near-surface scattering. As in the case of speckle noise in optics and acoustics, deterministic velocity model-building techniques cannot recover these heterogeneities which are much smaller than a wavelength. Conventional processing techniques struggle to perform when multiplicative noise remains unsuppressed. Although local and global stacking mitigates the effects of speckle noise, it leads to a severe loss of higher frequencies reducing the vertical resolution of the seismic data. The foundation for attacking speckle noise is a recently proposed mathematical model that includes two concurrent random multiplicative noise types: type 1 defining residual statics and type 2 describing random frequency-dependent phase perturbations that mimic small-scale near-surface scattering. Using this model, we have developed seismic time-frequency masking to suppress speckle noise on prestack...
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The growing popularity of land nodes demands careful survey design practices to smoothly supersede cabled seismic acquisition with geophone arrays. Unfortunately, trace density is often used as a catchall proxy to describe survey quality,... more
The growing popularity of land nodes demands careful survey design practices to smoothly supersede cabled seismic acquisition with geophone arrays. Unfortunately, trace density is often used as a catchall proxy to describe survey quality, which is a gross oversimplification. We describe comprehensive and quantitative workflows focusing on final image quality for evaluating existing or new 3D land acquisition geometries with arrays and single sensors. They streamline the design process, remove human bias, and close the loop between acquisition and processing. A central element is a data-driven approach for deriving absolute signal-to-noise ratio (S/N) directly from the data. The resulting S/N volumes can be analyzed as cubes or slices or distilled to statistical quantities. We apply new workflows to three typical use cases from 3D land seismic data. First, we quantitatively contrast different 3D data sets acquired with various field acquisition geometries and understand which acquisi...
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Time-lapse geophysical monitoring has potential as a tool for reservoir characterization, that is, for determining reservoir properties such as permeability. Onset times, the calendar times at which geophysical observations begin to... more
Time-lapse geophysical monitoring has potential as a tool for reservoir characterization, that is, for determining reservoir properties such as permeability. Onset times, the calendar times at which geophysical observations begin to deviate from their initial or background values, provide a useful basis for such characterization. We found that, in contrast to time-lapse amplitude changes, onset times were not sensitive to the exact method used to related changes in fluid saturation to changes in seismic velocities. As a consequence of this, we found that an inversion for effective permeability based upon onset times was robust with respect to variations in the rock-physics model. In particular, inversions of synthetic onset times calculated using Voigt and Reuss averaging techniques, but inverted using sensitivities from Hill’s averaging method, resulted in almost identical misfit reductions and similar permeability models. All solutions based on onset times recovered the large-scal...
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The growing popularity of land nodes demands careful survey design practices to smoothly supersede cabled seismic acquisition with geophone arrays. Unfortunately, trace density is often used as a catchall proxy to describe survey quality,... more
The growing popularity of land nodes demands careful survey design practices to smoothly supersede cabled seismic acquisition with geophone arrays. Unfortunately, trace density is often used as a catchall proxy to describe survey quality, which is a gross oversimplification. We describe comprehensive and quantitative workflows focusing on final image quality for evaluating existing or new 3D land acquisition geometries with arrays and single sensors. They streamline the design process, remove human bias, and close the loop between acquisition and processing. A central element is a data-driven approach for deriving absolute signal-tonoise ratio (S/N) directly from the data. The resulting S/N volumes can be analyzed as cubes or slices or distilled to statistical quantities. We apply new workflows to three typical use cases from 3D land seismic data. First, we quantitatively contrast different 3D data sets acquired with various field acquisition geometries and understand which acquisition parameters are likely responsible for S/N differences. Second, we perform a realistic numerical feasibility study evaluating multiple 3D acquisition geometries with arrays and single sensors and assess their expected performance on a complex SEG Advanced Modeling Arid data set representative of the desert environment. For feasibility studies, complete automation can be achieved by applying migration in lieu of processing and data-driven S/N as evaluation steps. Finally, we show how to predict absolute S/N outcomes of new 3D acquisitions based on the existing legacy data with different acquisition geometry. We demonstrate the excellent predictive power of the analytical signal-strength estimate formula for both field and synthetic elastic data sets. Translating survey design into commonly spoken "image S/N language" improves communication between geoscientists and enables more effective decision-making. This paper is an expansion of Bakulin et al. (2022c), originally presented at the Second International Meeting for Applied Geoscience & Energy.
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Even after sophisticated processing, land seismic data in complex areas exhibit weak and distorted prestack reflections with low coherency. Usually, the local stacking methods reveal clear reflections. However, the absolute level of... more
Even after sophisticated processing, land seismic data in complex areas exhibit weak and distorted prestack reflections with low coherency. Usually, the local stacking methods reveal clear reflections. However, the absolute level of amplitude spectra after such stacking experiences a substantial decline across the entire frequency band, reaching −10 to −25 dB. In addition, stacking leads to a significant and progressive loss of higher frequencies. We describe mathematical and intuitive physical models for multiplicative random noise that could consistently explain these field observations at least semiquantitatively. Multiplicative noise is represented by random timeshifts (residual statics) and random phase perturbations different for each frequency. Residual statics explain the progressive loss of higher frequencies. On the other hand, phase perturbations lead to a severe loss of coherency on prestack gathers and produce a strong downward bias or loss of broadband amplitudes after stacking. We find that both types of multiplicative noise can be physically generated by near-surface scattering layers with small-to-medium-scale geologic heterogeneities. We speculate that such multiplicative distortions can be referred to as seismic speckle noise well established in optics and ultrasonics. Furthermore, we derive the fundamental properties of how random multiplicative noise transforms while stacking. The first essential finding reveals that stacking produces an unbiased estimate of the clean signal phase. The second finding finds the mathematical relationship between the frequency-dependent loss of stacked amplitude and the standard deviation of residual statics and phase perturbations. These findings serve as a theoretical justification for the previously proposed methods of phase substitution and phase corrections and open the way to efficiently address random multiplicative noise in seismic processing. V420 Bakulin et al.
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Seismic speckle noise is the primary factor causing severe reflection distortions caused by small-scale near-surface scattering. As in the case of speckle noise in optics and acoustics, deterministic velocity model-building techniques... more
Seismic speckle noise is the primary factor causing severe reflection distortions caused by small-scale near-surface scattering. As in the case of speckle noise in optics and acoustics, deterministic velocity model-building techniques cannot recover these heterogeneities which are much smaller than a wavelength. Conventional processing techniques struggle to perform when multiplicative noise remains unsuppressed. Although local and global stacking mitigates the effects of speckle noise, it leads to a severe loss of higher frequencies reducing the vertical resolution of the seismic data. The foundation for attacking speckle noise is a recently proposed mathematical model that includes two concurrent random multiplicative noise types: type 1 defining residual statics and type 2 describing random frequency-dependent phase perturbations that mimic small-scale near-surface scattering. Using this model, we have developed seismic time-frequency masking to suppress speckle noise on prestack data. The time-dependent and non-surface-consistent nature of scattering noise dictates
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Processing seismic data from drillbit-generated vibrations requires a reliable source signature for correlation and deconvolution purposes. Recently, a land field trial has been conducted in a desert environment. A memory-based downhole... more
Processing seismic data from drillbit-generated vibrations requires a reliable source signature for correlation and deconvolution purposes. Recently, a land field trial has been conducted in a desert environment. A memory-based downhole vibration accelerometer has been used together with a more conventional top-drive sensor to continuously record the pilot signal from 590 to 8600 ft (180–2621 m). Past results indicate that seismic-while-drilling (SWD) data processed using the top-drive accelerometer exhibit good quality in the middle sections of the well but a reduced signal-to-noise ratio for shallow and deep sections. One of the main challenges in using the downhole pilot is a substantial drift of the downhole clock time. To resolve it, a novel automated time-alignment procedure using the GPS-synchronized signal of the top-drive sensor as a reference is applied. The downhole recording provides a source signature of better quality. In shallow sections of the well, it helps to overc...
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Processing seismic data from drillbit-generated vibrations requires a reliable source signature for correlation and deconvolution purposes. Recently, a land field trial has been conducted in a desert environment. A memory-based downhole... more
Processing seismic data from drillbit-generated vibrations requires a reliable source signature for correlation and deconvolution purposes. Recently, a land field trial has been conducted in a desert environment. A memory-based downhole vibration accelerometer has been used together with a more conventional top-drive sensor to continuously record the pilot signal from 590 to 8600 ft (180-2621 m). Past results indicate that seismicwhile-drilling (SWD) data processed using the top-drive accelerometer exhibit good quality in the middle sections of the well but a reduced signal-to-noise ratio for shallow and deep sections. One of the main challenges in using the downhole pilot is a substantial drift of the downhole clock time. To resolve it, a novel automated time-alignment procedure using the GPSsynchronized signal of the top-drive sensor as a reference is applied. The downhole recording provides a source signature of better quality. In shallow sections of the well, it helps to overcome the intense surface-related vibrational noise, whereas, in deeper sections, it provides a cleaner extraction of weaker signals from the polycrystalline diamond compact bits. Processing with the downhole pilot results in better surface seismic data quality than with a conventional top-drive sensor. Therefore, enabling the use of the synchronized downhole pilot signal is of crucial importance for SWD applications. Modern cost-effective near-bit vibrational sensors widely used for different nonseismic applications could be an effective acquisition solution, as shown in this study.
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Local traveltime operators are an effective way to describe local kinematic wavefronts. They are useful for many applications. One of them is nonlinear beamforming for enhancing the signal-to-noise ratio of challenging seismic data. The... more
Local traveltime operators are an effective way to describe local kinematic wavefronts. They are useful for many applications. One of them is nonlinear beamforming for enhancing the signal-to-noise ratio of challenging seismic data. The so-called 2+2+1 method is a pragmatic approach to estimate unknown local traveltime operators from input data. However, its efficiency still has much room for improvement when the solution space is big. We accelerate the 2+2+1 method using graphics processing unit (GPU) computing with the Compute Unified Device Architecture (CUDA) programming language. We detail the CPU- and GPU-based 2+2+1 search algorithms and demonstrate the efficiency improvement using synthetic and field data examples. Compared to a standard multi-core CPU implementation, our new GPU implementation achieves almost the same quality results at only ∼10% run-time cost.
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Research Interests: Geology and Tomography
Statics are an effective approach to correct for complex velocity variations in the near surface, but so far, to a large extent, a general and robust automatic static correction method is still lacking. In this paper, we propose a novel... more
Statics are an effective approach to correct for complex velocity variations in the near surface, but so far, to a large extent, a general and robust automatic static correction method is still lacking. In this paper, we propose a novel two‐phase automatic static correction method, which is capable of handling both primary wave statics (PP statics) and converted‐wave statics (S‐wave statics). Our method is purely data driven, and it aims at maximizing stacking power in the target zone of the stack image. Low‐frequency components of the data are analysed first using an advanced genetic algorithm to estimate seed statics and the time structure for an event of interest, and then the original full‐band data are further aligned via the back‐and‐forth coordinate descent method using the seed statics as initial values and the time structure for event alignment guidance. We apply our new method to two field datasets, i.e., one for 2D PP static correction and the other for 3D S‐wave static correction.
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Even after sophisticated processing, land seismic data in complex areas exhibit weak and distorted prestack reflections with low coherency. Usually, the local stacking methods reveal clear reflections. However, the absolute level of... more
Even after sophisticated processing, land seismic data in complex areas exhibit weak and distorted prestack reflections with low coherency. Usually, the local stacking methods reveal clear reflections. However, the absolute level of amplitude spectra after such stacking experiences a substantial decline across the entire frequency band, reaching −10 to −25 dB. In addition, stacking leads to a significant and progressive loss of higher frequencies. We describe mathematical and intuitive physical models for multiplicative random noise that could consistently explain these field observations at least semiquantitatively. Multiplicative noise is represented by random timeshifts (residual statics) and random phase perturbations different for each frequency. Residual statics explain the progressive loss of higher frequencies. On the other hand, phase perturbations lead to a severe loss of coherency on prestack gathers and produce a strong downward bias or loss of broadband amplitudes after...
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Distributed Acoustic Sensing (DAS), as a seismic sensor, has unique features allowing us to record multiple datasets with variable acquisition parameters set inside the recording box, while using one continuous recording cable and a... more
Distributed Acoustic Sensing (DAS), as a seismic sensor, has unique features allowing us to record multiple datasets with variable acquisition parameters set inside the recording box, while using one continuous recording cable and a single round of shooting. We reveal how these distinct features allow DAS to deliver multi-scale data and have the capability to focus on both the near surface and deeper targets simultaneously. We present synthetic and field examples of "deep" and "shallow" DAS surveys and demonstrate their effectiveness. The new capabilities of surface seismic with DAS technology comprise a sensing revolution that addresses long-standing near-surface issues in land seismic without compromising the deeper imaging. Achieving similar capabilities with point sensors could be done but would lead to ballooning acquisition costs, whereas surface seismic with DAS can deliver them at a cost less than conventional geophone acquisition available today.
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The initial quantification of data quality is an important step in seismic data acquisition design, including the choice of sensing strategy. The signal-to-noise ratio (SNR) often drives the choice of distributed acoustic sensing (DAS)... more
The initial quantification of data quality is an important step in seismic data acquisition design, including the choice of sensing strategy. The signal-to-noise ratio (SNR) often drives the choice of distributed acoustic sensing (DAS) parameters in vertical seismic profiling (VSP). We compare this established approach for data quality assessment with metrics comparing DAS data products to available well logs. First, we create kinematic and dynamic data products derived from original seismic data, such as the interval velocity and amplitude of P-wave arrivals. Next, we quantify the quality of derived data products using well log data by calculating various statistical metrics. Using a large dataset of 220 different VSP experiments with a fixed source location and various DAS acquisition parameters, such as gauge length (GL), conveyance type, and lead-in length, we analyzed the statistical distribution of various metrics. The results indicate the decoupling between seismic-based and ...
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Modern seismic acquisition is trending toward recording high-channel count data with smaller field arrays or single sensors. Reducing the size of field arrays leads to a deterioration of data quality. Many processing steps requiring... more
Modern seismic acquisition is trending toward recording high-channel count data with smaller field arrays or single sensors. Reducing the size of field arrays leads to a deterioration of data quality. Many processing steps requiring estimation of prestack parameters become more challenging due to the low signal-to-noise ratio (SNR) of the data. Conventional processing algorithms require estimation of velocities, statics, and surface-consistent scalars and deconvolution operators, and need good prestack data quality. This is rarely the case for land seismic data acquired in arid desert environments of Saudi Arabia with a complex near surface. We present two methods for prestack seismic signal enhancement based on utilization of neighboring traces. The first method, called supergrouping, performs local summation of traces using a global normal moveout correction to align reflected signals. The second approach, called nonlinear beamforming (NLBF), is a data-driven procedure for estimat...