Ocean Bottom Node Research Articles

Influence of shear velocity on elastic full-waveform inversion: Gulf of Mexico case study using multicomponent ocean-bottom node data

Elastic full-waveform inversion (FWI) is superior to acoustic FWI due to its ability to simulate complex mode conversions in fast-varying elastic media. Using elastic FWI may become important when building velocity models in areas of large complex salt bodies that we typically see in the Gulf of Mexico. Accounting for elastic effects in FWI can reduce the artifacts that are caused by using an acoustic approximation. We often rely on petrophysics relations to define an initial shear velocity model, which also could be challenging. We demonstrate how to take advantage of the reflected converted waves from the top of the salt interface recorded in horizontal geophones to improve the estimation of the background shear velocity. Then, we illustrate the impact of the initial background shear velocity in the elastic inversion of the long-offset low-frequency hydrophone data. The workflow is based on a combination of wave-equation traveltime inversion, to cope with the cycle skipping, and FWI, to obtain higher-resolution results.

Past geophysics science fair projects inspire new ideas in a high school STEM setting

During the 2020–2021 school year, a Bartlesville (Oklahoma, USA) High School student engaged in a science, technology, engineering, and math science fair project. It was inspired by a past science fair project published in The Leading Edge in November 2019. The goal of the project is to determine if a 3D seismic survey could be designed to provide even fold in the heart of an ocean-bottom node (OBN) seismic survey for converted waves with sources and receivers at different elevations. Much of the work involves the derivation of a generalized set of equations that predict the required bin size and expected fold for a given 3D OBN seismic survey design. Once the equations are established, a set of seismic survey design tests are conducted to determine if the equations are valid.

Applying wavelet transform to suppress ghost in ocean-bottom node dual-sensor technology

Applying wavelet transform to suppress ghost in ocean-bottom node dual-sensor technology

Nordkapp Topseis/Node Acquisition — Lessons from a Modelling Study

Based on an extensive 3D modelling study utilising full-wavefield Finite-Difference modelling and Full-Waveform Inversion (FWI) we demonstrate that the TopSeis/OBN hybrid acquisition acquired from May to August 2021 in the Nordkapp basin in the Barents Sea has the potential to image salt flanks and sedimentary details, given an accurate initial model in the shallow and a carefully designed deblending and FWI workflow. As a part of this we demonstrate that the large offsets and multi-azimuth recorded by the ocean bottom nodes are crucial to map the complex salt diapirism in the area including the steeply dipping flanks.

Separating Scholte Wave and Body Wave in OBN Data Using Wave-Equation Migration

The ocean bottom nodes (OBNs) acquire seismic data at a challenging depth to explore the subsurface structures. The recorded body wave and Scholte wave are highly mixed and are difficult to be separated. The strong body wave would influence the high-order modes extraction using the Scholte wave, while the Scholte wave would degrade the imaging of sedimentary structures using body wave. The lacking of effective methods for separating both waves prevents their application. We developed a migration-based method to accurately separate the Scholte wave and body wave in the OBN data. First, we use high-pass filtering to divide the original OBN data into three parts: background noise, high-frequency body wave, and the mixture of Scholte wave and low-frequency body wave. Then, we separate the Scholte wave and low-frequency body wave using migration and demigration based on the fact that they have different limits of reversible-migration velocity. Finally, we generate the separated body wave by subtracting the Scholte wave from the denoised OBN data. For the off-line data, the local orthogonalization method is required to retrieve the weak leakage of Scholte wave around the apices. Theoretical analyses and numerical experiments show that the proposed method can accurately separate Scholte wave and body wave without any visible artifacts while retaining most of their inherent properties. The separated body wave provides a high-quality input for imaging sedimentary structures, and the separated Scholte wave enables the extraction of high-order modes of dispersion curve that are crucial for high-resolution surface-wave inversion.

The Wolfspar experience with low-frequency seismic source field data: Motivation, processing, and implications

The promise of fully automatic full-waveform inversion (FWI) — a (seismic) data-driven velocity model building process — has proven elusive in complex geologic settings, with impactful examples using field data unavailable until recently. In 2015, success with FWI at the Atlantis Field in the U.S. Gulf of Mexico demonstrated that semiautomatic velocity model building is possible, but it also raised the question of what more might be possible if seismic data tailor-made for FWI were available (e.g., with increased source-receiver offsets and bespoke low-frequency seismic sources). Motivated by the initial value case for FWI in settings such as the Gulf of Mexico, beginning in 2007 and continuing into 2021 BP designed, built, and field tested Wolfspar, an ultralow-frequency seismic source designed to produce seismic data tailor-made for FWI. A 3D field trial of Wolfspar was conducted over the Mad Dog Field in the Gulf of Mexico in 2017–2018. Low-frequency source (LFS) data were shot on a sparse grid (280 m inline, 2 to 4 km crossline) and recorded into ocean-bottom nodes simultaneously with air gun sources shooting on a conventional dense grid (50 m inline, 50 m crossline). Using the LFS data with FWI to improve the velocity model for imaging produced only incremental uplift in the subsalt image of the reservoir, albeit with image improvements at depths greater than 25,000 ft (approximately 7620 m). To better understand this, reprocessing and further analyses were conducted. We found that (1) the LFS achieved its design signal-to-noise ratio (S/N) goals over its frequency range; (2) the wave-extrapolation and imaging operators built into FWI and migration are very effective at suppressing low-frequency noise, so that densely sampled air gun data with a low S/N can still produce useable model updates with low frequencies; and (3) data density becomes less important at wider offsets. These results may have significant implications for future acquisition designs with low-frequency seismic sources going forward.

Analysis of water velocity changes in time-lapse ocean bottom acquisitions - A synthetic 2D study in Santos Basin, offshore Brazil

Time-lapse seismic is an important tool for reservoir management. As seismic data quality improves, there is a drive for moving towards quantitative interpretation, which demands data of higher repeatability. In deep water time-lapse projects, the changes in the speed of sound of the water layer between baseline and monitor acquisitions play a significant role in the data processing. In this work, we study the effects of these water velocity changes, in a scenario of ocean bottom nodes (OBN) acquisition. We perform 2D elastic seismic modeling with high-resolution property models for two distinct survey dates. In each date, different water velocity profiles, measured in field experiments in a Brazilian Pre-salt area, are considered. To incorporate source and receiver non-repeatability, some differences in the acquisition geometries are also tested for each vintage. The synthetic data are compared in terms of time-lapse amplitudes, and repeatability is quantified via the normalized root mean squared attribute (NRMS). For the parameters considered in our study, the deterioration of NRMS seems to be dominated by the non-repeatability of the receivers and by water velocity variations, with source non-repeatability having a lower contribution. We believe the results presented in this work are a first step towards a more robust methodology for time-lapse feasibility studies, which incorporates imaging uncertainties and allows us to understand the contribution of each element that could affect the 4D seismic image quality.

Tupi Nodes pilot: A successful 4D seismic case for Brazilian presalt reservoirs

The oil and gas industry has established 4D seismic as a key tool to maximize oil recovery and operational safety in siliciclastic and low- to medium-stiffness carbonate reservoirs. However, for the stiffer carbonate reservoirs of the Brazilian presalt, the value of 4D seismic is still under debate. Tupi Field has been the stage of a pioneering 4D seismic project to field test the time-lapse technique's ability in monitoring production and water-alternating-gas (WAG) injection in the Brazilian presalt. Ocean-bottom node (OBN) technology was applied for the first time in the ultra-deep waters of Santos Basin, leading to the Tupi Nodes pilot project. We started with feasibility studies to forecast the presalt carbonate time-lapse responses. The minerals that constitute these carbonate rocks have an incompressibility modulus that is generally twice as large as those of siliciclastic rocks. This translates into discrete 4D signals that require enhanced seismic acquisition and processing techniques to be correctly detected and mapped. Consequently, two OBN seismic acquisitions were carried out. Time-lapse processing included the application of top-of-the-line processing tools, such as interbed multiple attenuation. The resulting 4D amplitude images demonstrate good signal-to-noise ratio, supporting both static and dynamic interpretations that are compatible with injection and production histories. To unlock the potential of 4D quantitative interpretation and the future employment of 4D-assisted history-matching workflows, we conducted a 4D seismic inversion test. Acoustic impedance variations of about 1.5% are reliably distinguishable beyond the immediate vicinity of the wells. These 4D OBN seismic surveys and interpretations will assist in identifying oil-bypassed targets for infill wells and calibrating WAG cycles, increasing oil recovery. We anticipate that studies of the entire Brazilian presalt section will greatly benefit from the results and conclusions already reached for Tupi Field.

True-amplitude migration through regularized extended linearized waveform inversion

The ability to create subsurface images whose amplitudes are proportional to the elastic wavefield variations recorded within seismic data as a function of reflection angle is fundamental for performing accurate amplitude-variation-with-offset (AVO) analysis and inversion. A process that generates such images is commonly referred to as true-amplitude migration. We have determined how the extended subsurface-offset image space is able to preserve the elastic behavior of the primary reflections when these events are acoustically migrated with a reverse time migration approach performed in a least-squares fashion. Using a single-interface model, we determine how the angle-domain image amplitude variations from an extended-offset acoustically migrated image closely follow the theoretical elastic Zoeppritz response even at the critical angle. Furthermore, we develop a subsalt synthetic test in which 1C ocean-bottom-node (OBN) data are used within a regularized linearized waveform inversion procedure. In this test, we highlight the ability of the acoustic extended-angle image domain to preserve the correct elastic amplitude variations of the reflected events from three subsalt sand lenses. Our method allows accurate inversion of elastic-wave data for subsurface parameter variations that are critical for reservoir characterization in oil and gas exploration and production. We determine its performance on an OBN field data set recorded in the Gulf of Mexico in which the AVO response of a potential gas-bearing prospect is correctly retrieved.

Extending subsurface imaging beyond ocean-bottom node coverage using multiples: A case study in deepwater Nigeria

We have evaluated the results of a receiver decimation study in a deepwater context using separated wavefield imaging (SWIM) algorithms to provide extended illumination for imaging without ocean-bottom node (OBN) positioning constraints. We carried out subsurface imaging using the SWIM imaging technique with a reduced OBN layout, and we compared the results with those from conventional one-way wave-equation migration. We found from the results that the SWIM algorithm makes it possible to reduce the OBN layout while obtaining a similar subsurface image with the same shot geometry, which allows a reduced receiver acquisition effort, offers more geometry flexibility without affecting the image quality, with a potentially significant reduction of acquisition cost and 4D processing turnaround time.

Benefits of using dense OBN for exploration: an example from Utsira using AI and machine learning

The first example of artificial intelligence (AI) geological interpretation on a large scale, densely sampled ocean bottom node (OBN) exploration dataset, Utsira OBN, is presented here. This entirely new suite of derivative seismic products provides enhanced exploration insights through AI, especially in areas where infrastructure led exploration (ILX) is drawing increased focus from the E&P industry. This work is complemented with a velocity model built with the latest processing technology: ultra-long offset and reflection FWI combined with tomography and anisotropy updates. The toolboxes, processing versus AI/ML, do not exclude or replace each other; a combined analysis can extract added value and reduce uncertainties. Such analysis is presented here.

Fast Least-Squares Reverse Time Migration of OBN Down-Going Multiples

Nowadays the ocean bottom node (OBN) acquisition is widely used in oil and gas resource exploration and seismic monitoring. Conventional imaging algorithms of OBN data mainly focus on the processing of up-going primaries and down-going first-order multiples. Up-going multiples and higher-order down-going multiples are generally regarded as noise and should be eliminated or ignored in conventional migration methods. However, multiples carry abundant information about subsurface structures where primaries cannot achieve. To take full advantage of multiples, we propose a migration method using OBN down-going all-order multiples. And then the least-squares optimization algorithm is used to suppress crosstalks. Finally, a phase-encoding-based migration algorithm is developed to cut down the computational cost by blending several common receiver gathers together using random time delays and polarity reversals. Numerical experiments on the complex Marmousi model illustrate that the developed approach can enlarge the imaging area evidently, reduce the computational cost effectively, and enhance the image quality by suppressing crosstalks and improving the resolution.

Denoising for full-waveform inversion with expanded prediction-error filters

Low-frequency data of less than 5 Hz are essential to the convergence of full-waveform inversion (FWI) toward a useful solution. They help to build the velocity model low wavenumbers and reduce the risk of cycle skipping. In marine environments, low-frequency data are characterized by a low signal-to-noise ratio (S/N) and can lead to erroneous models when inverted, especially if the noise contains coherent components. Often, field data are high-pass filtered before any processing step, sacrificing weak but essential signal for FWI. We have denoised the low-frequency data using prediction-error filters that we estimate from a high-frequency component with a high S/N. The constructed filter captures the multidimensional spectrum of the high-frequency signal. We expand the filter’s axes in the time-space domain to compress its spectrum toward the low frequencies and wavenumbers. The expanded filter becomes a predictor of the target low-frequency signal, and we incorporate it in a minimization scheme to attenuate noise. To account for data nonstationarity while retaining the simplicity of stationary filters, we divide the data into nonoverlapping patches and linearly interpolate stationary filters at each data sample. We apply our method to synthetic stationary and nonstationary data, and we find that it improves the FWI results initialized at 2.5 Hz using the Marmousi model. We also demonstrate that the denoising attenuates nonstationary shear energy recorded by the vertical component of ocean-bottom nodes.

A review of OBN processing: challenges and solutions

Abstract In the last decade, a significant shift in the marine seismic acquisition business has been made where ocean bottom nodes gained a substantial market share from streamer cable configurations. Ocean bottom node acquisition (OBN) can acquire wide azimuth seismic data over geographical areas with challenging deep and shallow bathymetries and complex subsurface regimes. When the water bottom is rugose and has significant elevation differences, OBN data processing faces a number of challenges, such as denoising of the vertical geophone, accurate wavefield separation, redatuming the sparse receiver nodes from ocean bottom to sea level and multiple attenuation. In this work, we review a number of challenges using real OBN data illustrations. We demonstrate corresponding solutions using processing workflows comprising denoising the vertical geophones by using all four recorded nodal components, cross-ghosting the data or using direct wave to design calibration filters for up- and down-going wavefield separation, performing one-dimensional reversible redatuming for stacking QC and multiple prediction, and designing cascaded model and data-driven multiple elimination applications. The optimum combination of the mentioned technologies produced cleaner and high-resolution migration images mitigating the risk of false interpretations.

Simultaneous joint migration inversion as a high‐resolution time‐lapse imaging method: Feasibility and robustness study

ABSTRACTThe conventional time‐lapse processing workflow is usually sensitive to the non‐repeatable uncertainties between different vintages caused by noise, acquisition designs and independent processing. Therefore, in order to reduce these non‐repeatable uncertainties, all the datasets are usually acquired from well‐sampled and well‐repeated acquisition surveys, and the independent processing is always carefully tailored to maximally reduce the non‐repeatable uncertainties during processing. Moreover, the conventional time‐lapse analysis method, based on a time‐shift map, is not always a good indicator of the actual velocity differences due to its local one‐dimensional subsurface assumption. In order to relax these rigid requirements and have a better velocity change indicator, a robust high‐resolution simultaneous joint migration inversion was proposed as an effective time‐lapse tool for reservoir monitoring. The method combines a simultaneous data‐processing strategy with the joint migration inversion method. Joint migration inversion is a full wavefield inversion method with a parameterization in terms of reflectivity and propagation velocity. The simultaneous strategy allows the baseline and monitor parameters to communicate and compensate with each other dynamically during inversion, thus, suppressing the non‐repeatable uncertainties during the time‐lapse processing. To investigate the feasibility of using high‐resolution simultaneous joint migration inversion in practice, some numerical experiments are conducted to test the dependence of high‐resolution simultaneous joint migration inversion on the quality of the time‐lapse datasets including the following aspects: random noise; sparse surveys; ocean bottom node versus streamer (different types of monitoring surveys); non‐repeated sources, including source positioning errors and non‐repeated source wavelets; spatial weighting operators in the L2‐norm penalty terms; and sensitivity to weak time‐lapse effects. All the experiments are carried on the basis of a realistic synthetic time‐lapse model based on the Grane field offshore Norway. These experiments show that high‐resolution simultaneous joint migration inversion is robust to random noise, survey sparsity, survey non‐repeatability, source positioning errors and source wavelet discrepancies. Furthermore, high‐resolution simultaneous joint migration inversion remains effective when the spatial weighting operators in the L2‐norm penalty terms are largely relaxed, and high‐resolution simultaneous joint migration inversion is capable of detecting weak time‐lapse changes (e.g. velocity changes down to 35 m/s).

Nonrepeatability effects on time-lapse 4D seismic full-waveform inversion for ocean-bottom node data

Full-waveform inversion (FWI) can be applied to time-lapse (4D) seismic data for subsurface reservoir monitoring. However, nonrepeatability (NR) issues can contaminate the data and cause artifacts in the estimation of 4D rock and fluid property changes. Therefore, evaluating and studying the NR effects on the 4D data and FWI results can help, for instance, discriminate inversion artifacts from true changes and guide seismic survey design and processing workflows. Using realistic reservoir models, data, and field measurements of NR, we find the effects of NR source-receiver position and seawater velocity changes on the data and the 4D FWI results. We show that ignoring these NR effects in the inversion can cause strong artifacts in the estimated velocity change models and thus should be addressed before or during inversion. The NR source-receiver positioning issue can be successfully addressed by 4D FWI, whereas the NR water velocity issue requires measurements or estimations of water velocities. Furthermore, we compare the accuracy and robustness of the parallel, double-difference, and central-difference 4D FWI methods to realistic NR ocean-bottom node data in a quantitative way. Parallel 4D FWI fails to capture geomechanical changes and also overestimates the aquifer layer changes with NR data. Double-difference 4D FWI is capable of recovering the geomechanical changes, but it is also sensitive to NR noises, generating more artifacts in the overburden. By averaging the forward and reverse bootstrap 4D estimates, central-difference 4D FWI is more robust to NR noises and also produces the most accurate 4D estimates.

Research on joint inversion method of seismic compressional and shear waves from ocean-bottom nodes

Research on joint inversion method of seismic compressional and shear waves from ocean-bottom nodes

Shenzi OBN: An imaging step change

The story of seismic imaging over BHP's Shenzi Gulf of Mexico production field follows the history of offshore seismic imaging, from 2D to 3D narrow-azimuth streamer acquisition and to its leading the wide-azimuth movement with the Shenzi rich-azimuth (RAZ) survey. Each RAZ reprocessing project over the last 15 years applied the latest processing technology, culminating in hundreds of scenario tests to refine the salt model, but eventually the RAZ data reached a technical limit. A new ocean-bottom-node (OBN) survey acquired in 2020 has produced a step-change improvement over the legacy RAZ image. The uplift can be attributed to several factors. First, an OBN feasibility and survey design study demonstrated that a core of dense nodes combined with sparse nodes would improve the accuracy and resolution of the full-waveform inversion (FWI) solution. Second, the OBN data acquired following the survey design and employing FWI as the main model-building tool realized the predicted improvement. The result was a substantial change to the complex salt model, verified by a salt proximity survey as well as other salt markers, and improvement in imaging over the entire field. In addition to the improvement arising from a more accurate FWI velocity model, the steep-dip imaging also benefited from the new full-azimuth and long-offset data. However, the best steep-dip and fault imaging comes from the FWI image, a direct estimation of reflectivity from the FWI velocity. As the maximum frequency used by FWI moves toward the maximum frequency of the final reverse time migration (RTM), the FWI image approaches the resolution necessary to compete as the primary interpretation volume. Its subsalt illumination surpassed that of the RTM and even the least-squares RTM volumes. These imaging improvements are providing a new understanding of the faults and stratigraphic relationships of the field.

The impact of acquisition geometry on full-waveform inversion updates

Full-waveform inversion (FWI) is a high-resolution model-building technique that uses the entire recorded seismic data content to build the earth model. Conventional FWI usually utilizes diving and refracted waves to update the low-wavenumber components of the velocity model. However, updates are often depth limited due to the limited offset range of the acquisition design. To extend conventional FWI beyond the limits imposed by using only transmitted energy, we must utilize the full acquired wavefield. Analyzing FWI kernels for a given geology and acquisition geometry can provide information on how to optimize the acquisition so that FWI is able to update the velocity model for targets as deep as basement level. Recent long-offset ocean-bottom node acquisition helped FWI succeed, but we would also like to be able to utilize the shorter-offset data from wide-azimuth data acquisitions to improve imaging of these data sets by developing the velocity field with FWI. FWI models are heading toward higher and higher wavenumbers, which allows us to extract pseudoreflectivity directly from the developed velocity model built with the acoustic full wavefield. This is an extremely early start to obtaining a depth image that one would usually produce in much later processing stages.

Offset-continuation-trajectory (OCT) data regularization to a 2D ocean bottom node (OBN): Full-wave inversion application

ABSTRACT. Estimating attributes for a better understanding of subsurface geological structures is essential in many seismic exploration and production stages. As a powerful seismic inversion tool, Full Waveform Inversion (FWI) has been widely used to estimate many of such attributes with high resolution. In many cases, however, real acquisitions cannot provide the quantity and density of traces required for optimal inversion results. Consequently, schemes to produce new traces by interpolation/extrapolation of neighboring available traces play a crucial role. Another challenge of using a real dataset in an inversion process is the presence of certain types of noises, which are inherent to the seismic acquisition process and can be treated, generally, by the use of a band-pass filter. This paper uses the Offset-Continuation-Trajectory (OCT) stacking method to generate new traces and include them in an Ocean Bottom Node (OBN) acquisition for non-deeper water. Furthermore, we also use the OCT method for dataset enhancement. Next, we test the FWI on the enhanced dataset and analyze the results. Our approach is applied to a synthetic dataset obtained from an OBN acquisition carried out on the 2D Marmousi model as a proof-of-concept. Several additional traces, simulated by the OCT procedure, have been included. Despite the recognized complexities of the Marmousi model, we have obtained very encouraging results.Keywords: regularization, full waveform inversion, signal-to-noise enhancement.Regularização de dados pelo método de trajetória de continuação de afastamento para uma aquisição 2D OBN: Aplicação na inversão de onda completaResumo. A estimação de atributos físicos é essencial em muitos estágios da sísmica de exploração. Como uma poderosa ferramenta de inversão sísmica, a inversão da forma de onda completa (FWI, do inglês full waveform inversion) tem sido amplamente utilizada para estimar tais parâmetros com alta resolução. Contudo, em muitos casos, uma aquisição real pode não ser capaz de fornecer uma quantidade de traços exigidos para a obtenção de bons resultados. Assim, métodos que produzem novos traços por interpolação/extrapolação a partir de traços vizinhos desempenham um papel fundamental no processo de inversão sísmica. Outra dificuldade é a presença de certos ruídos, inerentes ao processo de aquisição do dado sísmico, geralmente, tratados usando certos tipos de filtros, como um passa banda. Neste trabalho, usamos o método denominado trajetória de continuação do afastameto (OCT, do inglês offset-continuation trajectory) para regularizar traços e incluí-los no sistema de aquisição escolhido, neste caso, do tipo OBN (do inglês, ocean bottom node) para superfícies rasas. Além disso, o método aumenta a relação sinal-ruído. Aplicamos FWI nos resultados da regularização para analisar se o dado regularizado obtém melhorias na inversão. Como prova de conceito, nossa abordagem é aplicada para um dado sintético 2D produzido por uma aquisição OBN usando o modelo de velocidade Marmousi, reconhecido por apresentar certas complexidades geológicas. Os resultados obtidos confirmam que utilizar o método OCT traz benefícios tanto no processo da inversão quanto no processamento do dado sísmico.Palavras-chave: regularização, inversão da forma de onda completa, melhoria da relação sinal-ruído.