Acquisition Footprint Research Articles

Integrated Approach Optimizes Underground Gas-Storage Process

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 207941, “Underground Gas-Storage Process Optimization Using Integrated Subsurface Characterization, Dynamic Modeling, and Monitoring: A Case Study,” by Longxin Li, Yuan Zhou, and Limin Li, PetroChina Southwest Oil and Gasfield Company, et al. The paper has not been peer reviewed. _ The operator’s Xiangguosi (XGS) gasfield facility began underground gas storage (UGS) operations in a depleted gas field in southwest China in 2013. Following this initial period, the site was reassessed to increase deliverability safely during the winter months to meet future peak gas demand. The results of that analysis informed the resulting system design, in combination with fit-for-purpose reservoir-surveillance systems; caprock-seal recording pressure, rock deformation, and seismicity data in real time; and regular wellbore inspection. Introduction The XGS UGS facility currently operates in a previously depleted gas reservoir in Sichuan province. Its construction took place during the second half of 2011; cushion gas injection started in June 2013. Located in a high-tectonic-stress region, the geological setting of the XGS field is structurally complex and highly faulted and the targeted carbonate formation is heterogeneous and naturally fractured. When the studies described in the complete paper commenced in November 2019, the field hosted 22.80×108 m3 of working gas along with 19.80×108 m3 of cushion gas. As of May 2020, the reservoir had completed eight injection and six withdrawal cycles and delivered a maximum withdrawal rate of 21.96×106 m3/d. The UGS conversion plans required a revisit to analyze the possibility of increasing the withdrawal rate to 28.55×106 m3/d, thereby positioning better for future peak gas demand. The drilling of five new wells commenced in 2019. Planned Technical Approach The purpose of the study was to optimize the XGS UGS facility’s working gas capacity and improve operational performance throughout asset life. It was proposed to achieve this by 4D geomechanical and 3D dynamic flow-simulation models. The geomechanical model would hinge on an integrated subsurface characterization work flow combined with an advanced monitoring network tightly connected with the surface facility operation to ensure maximum containment and optimal injection and withdrawal rates and volumes. This holistic approach would aid in ascertaining optimal drawdown pressures to minimize rock fatigue and ensure operation of the UGS facility within safe pressure limits. Fully integrated Subsurface Characterization A detailed review of the existing petrophysical interpretation from wells calibrated with core analysis data was undertaken. Petrophysical interpretations from 29 wells were used to construct a reservoir classification and petrophysical property models. This led to the understanding that depositional facies were not the overriding control on reservoir quality in this case because the reservoir is highly affected by karstification, diagenesis, and fracturing. Prestack migrated seismic data was improved with acquisition footprint, noise, and multiple removal and then interpreted to map subsurface structure. The edited well logs were used to build synthetic seismograms. A complex structural model was created that included 22 stratigraphic zones and a detailed fault model within the main field structure, integrating stratigraphic data and log curves from all recently drilled wells.

Joint towed streamer and ocean-bottom-seismometer data multi-parameter full waveform inversion in acoustic-elastic coupled media

Short-offset towed streamer data, and sparse ocean-bottom seismometer (OBS) data are not conducive to applying multi-parameter full waveform inversion (FWI) in production. It is challenging to reconstruct deep velocity in the former, and the latter suffers from severe acquisition footprints. We developed a joint acoustic-elastic coupled full waveform inversion (J-AEFWI) method, in which towed streamer data and ocean-bottom seismometer data were used jointly to build P-wave and S-wave velocity models. A new joint objective function was established using the least-squares theory, and the joint acoustic-elastic coupled full waveform inversion method on the acoustic-elastic coupled equation was derived. The method can inject the residuals of the towed streamer data and the ocean-bottom seismometer data in time backward propagating to update P-wave and S-wave velocity models. The synthetic experimental results show that joint acoustic-elastic coupled full waveform inversion obtains more accurate results than when using these two types of data alone. Compared to using the towed streamer or ocean-bottom seismometer data alone, the joint acoustic-elastic coupled full waveform inversion method leads to better illumination of the deep background velocities and suppression of acquisition footprints. The results of joint acoustic-elastic coupled full waveform inversion were slightly better than those of the cascaded full waveform inversion strategy. To further demonstrate the benefit of the proposed method, we applied it to the field data, and better results are obtained as expected.

Unsupervised Seismic Footprint Removal With Physical Prior Augmented Deep Autoencoder

Seismic acquisition footprints appear as stably faint and dim structures and emerge fully spatially coherent, causing inevitable damage to useful signals during the suppression process. Various footprint removal methods, including filtering and sparse representation (SR), have been reported to attain promising results for surmounting this challenge. However, these methods, e.g., SR, rely solely on the handcrafted image priors of useful signals, which is sometimes an unreasonable demand if complex geological structures are contained in the given seismic data. As an alternative, this article proposes a footprint removal network (dubbed FR-Net) for the unsupervised suppression of acquired footprints without any assumptions regarding valuable signals. The key to the FR-Net is to design a unidirectional total variation (UTV) model for footprint acquisition according to the intrinsically directional property of noise. By strongly regularizing a deep convolutional autoencoder (DCAE) using the UTV model, our FR-Net transforms the DCAE from an entirely data-driven model to a \textcolor{black}{prior-augmented} approach, inheriting the superiority of the DCAE and our footprint model. Subsequently, the complete separation of the footprint noise and useful signals is projected in an unsupervised manner, specifically by optimizing the FR-Net via the backpropagation (BP) algorithm. We provide qualitative and quantitative evaluations conducted on three synthetic and field datasets, demonstrating that our FR-Net surpasses the previous state-of-the-art (SOTA) methods.

Joint elastic reverse time migration of towed streamer and sparse ocean-bottom seismic node hybrid data

Compared to 1C towed-streamer (TS) seismic exploration, 4C ocean-bottom seismic (OBS) node exploration has great advantages in complex structure imaging, lithology, and fluid identification using elastic waves. However, sparse spatial sampling of OBS node surveys highlights the problems of the imaging acquisition footprint, poor phase continuity, and low signal-to-noise ratio (S/N) with conventional elastic reverse time migration (ERTM) methods. Therefore, a solution of joint ERTM (J-ERTM) is proposed by combining sparse OBS node data with dense TS data. In the J-ERTM of the hybrid data, a novel weighted boundary condition combined with acoustic-elastic coupling equations and a vector-based crosscorrelation imaging condition are presented to perform PP and PS imaging by receiver-side tensorial extrapolation of TS and OBS node hybrid data. A synthetic example demonstrates that our method can effectively process TS and OBS node hybrid data and improve elastic imaging problems caused by OBS node sparse acquisition. J-ERTM techniques also are applied to an active-source OBS data set from the South China Sea. To improve the imaging quality with limited data, some preprocessing procedures for field TS and OBS node hybrid data sets are necessary, such as denoising, OBS node relocation, OBS node orientation correction, OBS node calibration, and others. After preprocessing, the pressure component and velocity components have a more physical energy relationship, more consistent frequency range and wavelet, and a higher S/N. Finally, the preprocessed hybrid data can be used for J-ERTM. The imaging results demonstrate that our method works well with field data.

Improved Low-Rank Tensor Approximation for Seismic Random Plus Footprint Noise Suppression

Random plus footprint noise provokes severe seismic image deterioration and makes it challenging for interpreters to recognize and analyze accurate subsurface responses. Thus, as an elementary and indispensable preprocessing step, diverse footprint removal approaches, including filtering in the frequency or time-frequency domain and dictionary learning (DL), have been documented to achieve promising results in tackling this challenge. However, the prevailing denoising methods tend to treat 3-D seismic data as images for processing, but such flattening or matricization operations inevitably obliterate the three-dimensional image structures concealed in noisy observational seismic data, which hinders the removal performance of these approaches. To resolve this issue, this article proposes a new tensor model for 3-D seismic random plus footprint noise suppression, and this model is based on unidirectional total variation regularized low-rank tensor approximation (UTV-LRTA). In this model, UTV regularization is imposed to obtain the innately structural and directional behavior of the acquisition footprint. In this way, the footprint is removed by effectively decomposing the footprint-contaminated seismic image into a footprint-free image and a footprint component by UTV. In contrast, random noise is mitigated by regularizing the low-rankness of the third-order seismic tensors using the tensor nuclear norm. Moreover, a simple and powerful optimization algorithm based on the split Bregman iteration is introduced to resolve the proposed UTV-LRTA model. The suggested model is thoroughly assessed on synthetic and field datasets and significantly surpasses the state-of-the-art approaches quantitatively and qualitatively evaluated in the analyzed field examples.

3D reflection seismic imaging of volcanogenic massive sulphides at Neves‐Corvo, Portugal

AbstractThree‐dimensional reflection seismic data from the Neves‐Corvo area, southern Portugal, were reprocessed with the main objective of improving the seismic signature of the Lombador and Semblana volcanogenic massive sulphide deposits. The sensitivity for choosing adequate parameters for targeted imaging, even during the pre‐processing stage, such as common‐depth point binning size, was studied in detail before the main processing work began helping to optimize bin size parameters; preliminary stacking results from this analysis presented severe acquisition footprint, and seismic targets were not clearly identifiable. Processing results using pre‐stack dip move‐out and post‐stack migration methods show strong moderate to steeply dipping reflections. Several of the observed reflections can be correlated with known lithological contacts, some of which are interpreted to originate from the Semblana and Lombador deposits. Despite the mixed signal‐to‐noise ratio, the seismic cube reveals both shallow and deep three‐dimensional structures, allowing to account for the deposits’ lateral extension beyond the capabilities of two‐dimensional seismic imaging alone. Given the data processing approach taken it was possible to distinguish strong diffraction patterns, interpreted as originating from faults and edges of the Lombador deposit, illustrating the usefulness of diffraction patterns for better interpretation of geological features in hard‐rock environments.

An integrated study on fracture prediction using 3D P-wave field seismic data

An integrated study on fracture prediction by analyzing seismic anisotropy within a 3D P-wave seismic data set from an oilfield in Northwest China is performed. The research area is dominated by a regional anticline and the target layer is a fractured gas reservoir at a depth of approximately 3 km under the anticline. Two major aspects are considered. First, two P-wave poststack attributes (reflection strength and frequency content in selected lines) are extracted and their features in the target layer are examined, looking for the possible fracture distribution in two prospective zones. Second, the azimuthal attribute analysis approach is applied to estimate fracture density and orientation in the whole area from the prestack data (amplitude and traveltime). The result from the poststack data indicates the high possibility of fracture distributions in these two zones, and the prediction from azimuthal amplitudes in the prestack data is consistent with the fracture orientation from the well interpretation and the observation of outcrops at the top of the anticline but suffers from a poor offset-depth ratio and acquisition footprint. The prediction from azimuthal traveltime is strongly influenced by the regional anticline structure and, therefore, is not reliable. Nevertheless, the prediction from post- and prestack attributes provides more details of the fracture distribution in the target reservoir, which can expand understanding of the reservoir fracture distribution.

Channel boundary detection using partial area effect with sub-pixel resolution

Channel facies, of the most prevalent stratigraphic features, are essential from the perspective of hydrocarbon exploration. However, measuring edge features using the gradient vector's calculation in an individual pixel mainly produces edge borders with pixel resolution even in images with low noise levels. This paper introduces a novel seismic attribute based on the partial area effect algorithm assuming a particular discontinuity in the edge location to extract the buried channel boundaries. First, the Sobel-based edge detector extracts the pixels' partial derivatives as probable channel boundaries. Then, the direction and the dimension of the postulated partial area effect mask in the local maxima points are deliberated to elicit the edge curve coefficients as the perfect edge positions. The proposed algorithm was implemented on a synthetic time slice comprising two-channel events with varying thicknesses and sinuosity. The procedure was also investigated on two high-cut frequency filtered datasets from the Penobscot prospect in the Nova Scotia Basin accommodating canyon-channel events. The proposed algorithm was then compared to the prominent gradient-based edge detectors (Canny, Prewitt, and Sobel) and some conventional seismic attributes (apparent dip, most negative curvature, and similarity). The results showed that applying the nominated algorithm could provide an improved map of buried channels less affected by the coherent noise and acquisition footprints. The partial area effect algorithm also successfully localized more true-positive edge points and fewer false-positive ones in the synthetic and field seismic data examples.

A dictionary learning method with atom splitting for seismic footprint suppression

The acquisition footprint causes serious interference with seismic attribute analysis, which severely hinders accurate reservoir characterization. Therefore, acquisition footprint suppression has become increasingly important in industry and academia. We have assumed that the time slice of 3D poststack migration seismic data mainly comprises two components: useful signals and the acquisition footprint. Useful signals describe the spatial distributions of geologic structures with local piecewise smooth morphological features. However, the acquisition footprint often behaves as periodic artifacts in the time-slice domain. In particular, the local morphological features of the acquisition footprint in marine seismic acquisition appear as stripes. Because useful signals and the acquisition footprint have different morphological features, we can train an adaptive dictionary and divide the atoms of the dictionary into two subdictionaries to reconstruct these two components. We have devised an adaptive dictionary learning method for acquisition footprint suppression in the time slice of 3D poststack migration seismic data. To obtain an adaptive dictionary, we use the K-singular value decomposition algorithm to sparsely represent the patches in the time slice of 3D poststack migration seismic data. Each atom of the trained dictionary represents certain local morphological features of the time slice. According to the difference in the variation level between the horizontal and vertical directions, the atoms of the trained dictionary are divided into two types. One type significantly represents the local morphological features of the acquisition footprint, whereas the other type represents the local morphological features of useful signals. Then, these two components are reconstructed using morphological component analysis based on different types of atoms, respectively. Synthetic and field data examples indicate that our method can effectively suppress the acquisition footprint with fidelity to the original data.

Faults resembling channel-like features

We analyzed a synthetic transfer zone and its associated fault planes and relay ramp in Penobscot, a potential offshore field in the Scotian Basin. Transfer zones are structural areas where one fault dies out and another fault begins, forming a relay ramp in the middle. They can be categorized as divergent, convergent, and synthetic transfer zones depending on the relative location and dipping directions of the faults. These zones not only play an important role in fluid migration but also help interpreters delineate secondary features such as fractures, splay shears, and Riedel faults. Commonly, those faults would branch into smaller splays and the relay ramp can get “breached” with connecting faults with the increase of slip. The study area in the Scotian Basin is characterized by two major listric normal faults dipping in the same direction giving rise to a synthetic transfer zone. These faults are clearly visible on seismic attributes, including curvature and coherence slices extracted along the top of the Cretaceous Petrel Formation. However, when analyzing the seismic attributes along the overlying Wyandot Formation’s top, we observe channel-like features, which run parallel as well as at an angle to these faults. However, when we performed further analysis using seismic amplitude’s vertical slices, interpreted horizons, and seismic attributes, we found that these features are not channels. We divided the features into two types: The first type is parallel to the main faults and can be associated with the grabens formed by synthetic and antithetic secondary faults (northeast–southwest); the second type is related to the polygonal faulting associated with differential compaction and gravitational loading of the Wyandot Chalk Formation. Apart from the two lineations, there are north-northeast–south-southwest-oriented lineations, which are an impression of basement faulting, and north-northwest–south-southeast-oriented lineations representing the acquisition footprint. Geological feature: Synthetic and antithetic faults in a synthetic transfer zone Seismic appearance: Channel-like feature on seismic attribute horizon slices Alternative interpretations: Channels Features with similar appearance: Steep slope channels Formation: Wyandot Age: Late Cretaceous Location: Penobscot, Nova Scotia, Canada Seismic data: Open-source SEG Analysis tools: Coherence and curvature attributes

Migration using sea surface-related multiples: Challenges and opportunities

In marine geophysical exploration using seismic data, sea surface-related multiples can be used for imaging and producing extra illumination. However, the imaging of multiples can involve challenges related to acquisition and migration. The acquisition offset, trace spacing, and towing direction are all key factors that control the quality of imaging using multiples. The migration algorithm also affects its successful implementation. Ultimately, the objective of imaging using multiples is not to replace imaging using primaries; instead, imaging using multiples augments conventional migration when the imaging of primaries suffers from illumination issues. The imaging of multiples has the potential to mitigate shallow acquisition footprints and provide high-resolution shallow images, allowing the identification of drilling hazards and a reduction in drilling risks. Additionally, the imaging of multiples can provide high-resolution illumination of complex structures along salt boundaries, which is valuable for velocity model building. Moreover, this technique has the potential to reduce exploration expenses when applied with ocean-bottom seismic data.

Time-lapse resistivity imaging: CSEM-data 3-D double-difference inversion and application to the Reykjanes geothermal field

SUMMARY Time-lapse resistivity tomography bring valuable information on the physical changes occurring inside a geological reservoir. In this study, resistivity monitoring from controlled source electromagnetics (CSEM) data is investigated through synthetic and real data. We present three different schemes currently used to perform time-lapse inversions and compare these three methods: parallel, sequential and double difference. We demonstrate on synthetic tests that double difference scheme is the best way to perform time-lapse inversion when the survey parameters are fixed between the different time-lapse acquisitions. We show that double difference inversion allows to remove the imprint of correlated noise distortions, static shifts and most of the non-linearity of the inversion process including numerical noise and acquisition footprint. It also appears that this approach is robust against the baseline resistivity model quality, and even a rough starting resistivity model built from borehole logs or basic geological knowledge can be sufficient to map the time-lapse changes at their right positions. We perform these comparisons with real land time-lapse CSEM data acquired one year apart over the Reykjanes geothermal field.

GO_3D_OBS: the multi-parameter benchmark geomodel for seismic imaging method assessment and next-generation 3D survey design (version 1.0)

Abstract. Detailed reconstruction of deep crustal targets by seismic methods remains a long-standing challenge. One key to address this challenge is the joint development of new seismic acquisition systems and leading-edge processing techniques. In marine environments, controlled-source seismic surveys at a regional scale are typically carried out with sparse arrays of ocean bottom seismometers (OBSs), which provide incomplete and down-sampled subsurface illumination. To assess and minimize the acquisition footprint in high-resolution imaging process such as full waveform inversion, realistic crustal-scale benchmark models are clearly required. The deficiency of such models prompts us to build one and release it freely to the geophysical community. Here, we introduce GO_3D_OBS – a 3D high-resolution geomodel representing a subduction zone, inspired by the geology of the Nankai Trough. The 175km×100km×30km model integrates complex geological structures with a viscoelastic isotropic parameterization. It is defined in the form of a uniform Cartesian grid containing ∼33.6e9 degrees of freedom for a grid interval of 25 m. The size of the model raises significant high-performance computing challenges to tackle large-scale forward propagation simulations and related inverse problems. We describe the workflow designed to implement all the model ingredients including 2D structural segments, their projection into the third dimension, stochastic components, and physical parameterization. Various wavefield simulations that we present clearly reflect in the seismograms the structural complexity of the model and the footprint of different physical approximations. This benchmark model is intended to help to optimize the design of next-generation 3D academic surveys – in particular, but not only, long-offset OBS experiments – to mitigate the acquisition footprint during high-resolution imaging of the deep crust.

Approximating the Gauss–Newton Hessian Using a Space-Wavenumber Filter and its Applications in Least-Squares Seismic Imaging

The acquisition footprint, finite-frequency source, and unbalanced subsurface illumination make it difficult for traditional adjoint-based migration to produce a high-quality image for complex structures. By fitting reflection events with linearized simulation data, least-squares migration (LSM) can iteratively incorporate the effects of the Gauss–Newton Hessian (GNH) to produce high-quality depth profiles. However, high computational costs of forward and adjoint simulations limit the LSM applications in production. In this study, we present an efficient approximation approach for the GNH and utilize it as a preconditioner for the misfit gradient of the LSM to accelerate its convergence. The analytic solution of the GNH in homogeneous media reveals that the columns of the GNH are local spatial functions. Based on this observation, we design a space-wavenumber filter to approximate the GNH for heterogeneous media, which can be efficiently computed with the S-transform and spectral division. The mixed-domain property of this filter allows it to automatically take the wavenumber dependence of the GNH into account and, therefore, helps to improve spatial resolution. Numerical examples demonstrate that the approximated GNH can considerably improve the image quality and speed up the convergence of the LSM.

Impact of 5D regularization and interpolation on subsurface imaging: A case study of Stratton field, South Texas, United States of America

This case study aims to determine the effect of five-dimensional regularization and interpolation on seismic subsurface imaging, particularly focusing on impacts to noise attenuation, velocity analysis, and migration. Advanced seismic processing requires high fold coverage and regular cross-spread data to attain good noise attenuation and common offset vectors for appropriate migration. Complex geological scenarios pose substantial challenges for subsurface imagers and interpreters. Stratton Field, USA, contains a major fault, Agua Dulce, along with many smaller faults and thus requires dense acquisition for high-resolution subsurface imaging to reduce migration smiles. Data were processed twice, the first migration without 5D regularization and interpolation and the second with 5D regularization and interpolation. The migration without 5D regularization and interpolation was found to suffer from acquisition footprints, migration smiles and a lack of amplitude versus offset (AVO) behavior, whereas the subsurface image was enhanced with 5D regularization and interpolation and improved in terms of AVO behavior.

Target-oriented model-based seismic footprint analysis and mitigation

Compensating for the effects of an acquisition footprint can be one of the most daunting problems when using seismic attributes for quantitative interpretation. This is especially true for unconventional plays because they are on land with accompanying irregular acquisition geometries. Additionally, in such plays, the physical property changes are often small, making the seismic amplitude fidelity critical. We have developed a methodology that integrates a 1D elastic prestack synthetic model with 3D acquisition geometry to accurately model the seismic footprint produced by irregular or insufficient sampling of primary reflectivity. The stacked amplitude response of the modeled survey is then used to mitigate the poststack footprint on the field seismic. Modeling and removing this element of the acquisition footprint quantitatively improve the interpretive value of the mapped seismic amplitudes. In our study area, correlation between seismic amplitudes and well control increased from an [Formula: see text] of 0.053 before correction to an [Formula: see text] of 0.629 after. Our approach is especially effective in situations in which the spatial frequency of the footprint overlaps that of the geologic signal. Geological feature: Acquisition related seismic amplitude artifacts Seismic appearance: Smoothly varying amplitude changes Alternative interpretations: Bed thickness variation Features with similar appearance: Carbonate porosity Formation: Niobrara Formation, mixed chalks and marlstones Age: Upper Cretaceous Location: Wattenberg Field, Denver Basin, north central Colorado Seismic data: Joint acquisition between Anadarko Petroleum and Colorado School of Mines, Reservoir Characterization Project Analysis tools: Elastic prestack seismic modeling

Footprint Determination of a Spectroradiometer Mounted on an Unmanned Aircraft System

Unmanned aircraft system (UAS)-mounted spectroradiometers offer a new capability to measure spectral reflectance and solar-induced chlorophyll fluorescence at detailed canopy scales. This capability offers potential for upscaling and comparison with airborne and space-borne observations [e.g., the upcoming European Space Agency (ESA) Fluorescence Explorer (FLEX) satellite mission]. In this respect, the accurate spatial characterization and georeferencing of the UAS acquisition footprints are essential to unravel the origin and spatial variability of optical signals acquired within the extent of airborne/satellite pixels. In this article, we present and validate a novel algorithm to georeference the footprint extent of a nonimaging spectroradiometer mounted on a multirotor UAS platform. We used information about the spectroradiometer position and orientation during flight and about topography of observed terrain to calculate the footprint geolocation. In a recursive process, the field of view (FOV) of the spectroradiometer projected on the ground. Multiple FOV ground projections retrieved during a spectroradiometer reading (i.e., a single integration time) were aggregated to calculate the footprint extent. The spatial accuracy of the footprint geolocation was validated by applying the georeferencing algorithm on checkpoint pixels of image acquired with a comounted digital camera. Geolocations of the checkpoint pixels, which served as a proxy for the spectroradiometer footprint, were successfully compared with surveyed ground checkpoints. Finally, the spectral and radiometric quality of UAS-acquired reflectance signatures was compared with ground-measured reflectance of four natural targets (three different types of grass and a bare soil), and a strong agreement was observed.

Extraction and characterization of faults and fractures from 3D VSP data in a carbonate reservoir: A workflow

We present a workflow for the extraction and characterization of fractures and faults using a Reverse Time Migrated (RTM) volume from 3D Vertical Seismic Profile data (3D VSP) acquired in an oilfield offshore Abu Dhabi in the United Arab Emirates. The workflow consists of: preconditioning of the input RTM volume, which involves removal of acquisition footprints; extraction of faults and fractures using a semblance based discontinuity attribute; binary filtering and clustering for characterization and interpretation using prior geological information, as well as removals of unwanted features such as those related to stratigraphy; and finally interpretation. Complex networks of lineaments were extracted after application of the workflow. The location of lineaments with length greater than 200 m and orientated WNW-ESE to NW-SE correlates with a known flower structure which has a trend similar to that of the Proterozoic Najd Fault System that cut the Arabian Peninsula. Lineaments with strike directions ENE-WSW and NE-SW are interpreted to be related to reactivation of basement faults and correspond to the Hormuz Salt basin's major trend in the Arabian Gulf. Dominant strike directions of lineaments at three reservoir levels correlate with dominant strike directions of interpreted fractures from Fullbore Formation Microimager (FMI) and core data; thus implying that they are likely related to fractures or fracture corridors. Lineaments with orientation NNE-SSW correlate with closed fractures while lineaments with orientation NNW-SSE correlate with open fractures. Zones with relatively high fracture intensity are generally located north and north-west of the VSP well in the reservoir zones. The good correlation of the results with interpreted fractures from core and FMI data shows the robustness of the workflow and gives confidence to the results.

Near-surface site investigation by seismic interferometry using urban traffic noise in Singapore

We have evaluated a field test in the city of Singapore to assess the feasibility of the passive seismic survey for bedrock depth determination and to further investigate the optimal acquisition parameters. The ambient noise field, dominated by urban traffic noise, is recorded passively for the application of seismic interferometry. Spectral analysis indicates that the traffic-induced noise by local roads is concentrated between 3 and 25 Hz. We use multiple signal classification beamforming for wavefield direction of propagation analysis. We apply seismic interferometry to retrieve the surface-wave part of the Green’s functions, based on which surface-wave dispersion relations are extracted and further inverted for 1D S-wave velocity profiles. Subsequently, we compare the inversion results from seismic interferometry with borehole logs at multiple sites in Singapore and establish that the bedrock depths are well-determined using passive seismic methods within a maximum error of 3 m. By investigating the convergence of the crosscorrelograms, we ascertain that the best compromise of cost, efficiency, and accuracy for a passive site investigation in Singapore can be achieved in 15 min in the morning of a working day using an array as short as 30 m with six vertical geophones, although these parameters should be reinvestigated at other sites and other times. The success of this case study demonstrates that accurate near-surface site investigation can be achieved with faster acquisition, fewer receivers, and a smaller acquisition footprint compared with conventional methods, all of which improve the efficiency particularly in a highly developed urban environment.

Variogram modeling of broadband artifacts of a seafloor map for filtering with Factorial Kriging

Accurate seafloor maps are critical in offshore petroleum projects. Almost all subsurface modeling workflows use these maps: for example, pore pressure models and reservoir geomechanics. These studies generally involve sums of properties along the vertical, consequently, noise or acquisition artifacts at the seafloor map tend to propagate and even amplify in the subsequent models. Seafloor maps are normally acquired by sound-sensing technology and related procedures, which expectedly introduce noise and artifacts. Moving window filters, such as average and median filters, are easy to use and fast to compute, hence they are used very often by interpreters to make geologically sound horizons. However such filters are unable to discern noise, artifacts and signal, resulting in the compromise of actual information. Filtering in the frequency domain can pose difficulties when noise, artifacts and geological information overlap in the frequency domain, as the total energy tend to concentrate in the lowest frequencies. Factorial kriging (FK) is a spatial filter that yields separate estimations, each corresponding to a variogram nested structure. FK relies on the principle that structurally complex information is a sum of independent information components while the variogram is a clear and reliable way to select the frequency ranges of each component. Hence, this method can effectively separate acquisition artifacts from seafloor information based on their different spatial structures modeled with variograms. This work investigates an application of FK for filtering of hard-edged (broadband) artifacts in post-processed interpreted seismic data. Differently from random noise, artifacts are spatially correlated information components mixed with actual geologic information. Initially, removal of the bathymetric trend makes the case stationary for a high-resolution variogram map computed in the frequency domain via fast Fourier transform (FFT), which enables a full 2D variogram modeling. Theoretical variogram surfaces are fit to the experimental variogram map, enabling the identification and modeling of a set of nested variograms. The authors envisaged search strategies to select a small number of informative samples to reduce kriging runtime and, at the same time, cover the necessary spatially correlated variability. A workflow on a large seismic-derived seafloor 2D map is demonstrated, detailing each step with emphasis on the sensitive variogram modeling step, followed by search strategy definition and choice of the geology-bearing factors for seafloor restoration. Filtering in frequency domain was performed for comparison. Results showed that broadband artifacts require a non-traditional approach to variogram modeling, which was performed in a second FK run with a wholly new variogram model. The filtering operations revealed seafloor features, which were previously unseen in the original map, and the final result was similar to that obtained with FFT. FK is a lossless filtering technique that is a highly effective method to remove acquisition footprints in final grids and volumes in which acquisition geometry information is not available. 11FFT – fast Fourier transform22FK – Factorial Kriging33KT – Kriging with a trend44TCL – Tool Command Language