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EAGE 2020 Annual Conference & Exhibition Online
- Conference date: December 8-11, 2020
- Location: Online
- Published: 08 December 2020
81 - 100 of 368 results
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Organic Geochemical Characteristics of Source Rock in Doseo Depression of Central African Rift System
More LessSummaryDoseo depression is an underexplored frontier onshore zone, belonging to Central African Rift System. To evaluate the source rock of the depression, we took 112 shale cuttings and 6 oil samples for pyrolysis, elements analysis, vitrinite reflectance, macerals identification, carbon isotopes and mass spectrometry analysis. The results show that three sets of high-quality lacustrine oil-prone source rocks are continuously developed in the Lower Cretaceous of Doseo depression. The organic matter type of three source rock are mainly I-II1, of which Kedeni source rock has the best quality. The maturity of Kedeni source rock is low to medium in the edge of the depression, but in the center of the depression it probably reach the high mature level. Based on the widespread effective source rock in the Doseo depression, the resource potential is considerable in the interbedded sandstone reservoirs of Lower Cretaceous.
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Elastic Full Waveform Inversion for Sub-Basalt Imaging
Authors A. Stopin, R. Plessix and S. BerglerSummaryTraditional model building techniques are challenged by the complexity of the wavefield in volcanic basin and finite frequency approach should be preferred. In view of the large velocity contrast observed at the top and base volcanic, elastic effects may occur. We apply FWI to build a velocity model for a narrow azimuth slanted streamer data set acquired in the North Atlantic margin. Both acoustic and elastic FWI are run to evaluate the severity of the elastic effects. The fit with the data after the inversion is good for both the acoustic and elastic inversions, but the acoustic velocity model shows fast velocity artifacts like the ones usually observed above salt interfaces. The migrated images and the pre-stack gather confirm that the elastic inversion result is superior to the initial model and the to the acoustic model obtained by inversion. Elastic FWI can reconstruct a complex velocity model with wavelength size variations of large magnitude and can potentially be the tool of choice for allowing imaging under volcanic layers.
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The Use of Imaging Techniques to Understand CO2-Water-Rock Interaction in Depleted Carbonate Field, Offshore Sarawak Malaysia
Authors W.P. Yong, S.S. Md Shah and W.M.L. SazaliSummaryField C is a depleted gas field with more than 20 years of production. It is identified as a potential CO2 storage site based on containment, well integrity and storage injectivity/capacity ranking. To ensure the feasibility of Field C as a CO2 storage site, the R&D team has conducted a set of static batch geochemical reaction experiments to evaluate the effects of CO2–brine-rock kinetic reaction and mineralogy changes due to potential mineral dissolution and/or precipitation using imaging techniques. The original and after CO2 exposure analysis of the core and water samples are conducted using QEMSCAN, digital core analysis and ICP water analysis with the following observations, (1) slight increase of porosity is observed from sample A (1.096%) and sample B (0.47%); (2) The amount of geochemistry reactions in gas zone is more than aquifer zone (3) 4 wt% calcite mineral increment for sample A and 0.43 wt% calcite mineral reduction from sample B. Overall, there is no significant changes after 45 days of CO2 ageing and it is preferable to inject CO2 in aquifer zone than gas zone for Field C.
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Efficient 1D Laplace-Fourier FWI of Land Seismic Data
Authors E. Sandoval Curiel, D. Colombo, A. Kontakis and D. RovettaSummaryImaging the subsurface with land seismic data requires a high resolution model of the near-surface. Conventional methodologies produce inaccurate results in the presence of velocity inversions. Full waveform inversion (FWI) is able to reconstruct these velocity variations, but is computationally expensive and is ineffective in areas of poor seismic data quality. We obtained an accurate near-surface velocity model in a complex wadi structure previously studied. To achieve this, we employed the recently developed 1.5D version of Laplace-Fourier acoustic FWI coupled to an automatic method for near-surface analysis.
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Detection of Gas Leakage from the Deep-Seated Reservoir Using Multi-Attribute Analysis in Poseidon, NW Shelf, Australia
More LessSummaryAccurate delineation of hydrocarbons seepage, accentuate the hydrocarbons migration pathways, seal integrity clue and alleviate drilling hazards. In order to evaluate hydrocarbons seepage, knowledge of migration pathways and its source is essential. Many authors have reported events of gas leakage in the Poseidon area however, it has never been investigated in detail to confirm the origin of the gas leakage. This study analyses the relationship between migration pathways and the deeper reservoir present in that area from full stacked 3D seismic data using multi-attribute analyses together with state-of-the-art artificial neural networks.
This study concluded that the deep reservoir of Jurassic age (i.e., Plover formation) is acting as the source of gas migration hence, it confirmed that hydrocarbons are leaking from the existing reservoir. Connectivity between gas clouds and pockmarks is evident from the processed gas chimney cube, which indicates that it’s an active seep system. The results obtained from the processed chimney cube are validated using the Spectral decomposition. The existence of gas chimney is also validated by a new approach like using a cross plot between “lamda-rho” and gas chimney probability values. The results of this study will provide significant input for hydrocarbon prospect evaluation of the region.
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Designing High Density Land Acquisition Surveys in Complex Environments; A Case Study from East Siberia, Russia
Authors J. Naranjo, N. Gurentsov, D. Tverdokhlebov, O. Adamovich and R. MelnikovSummaryEast Siberia, Russia is a vast, primarily underexplored area with prolific hydrocarbon potential. Some of the reasons for limited exploration can be attributed to its remoteness and to the extreme complexity of the surface and near surface conditions. While high density seismic acquisition techniques have been widely proven in open access areas where source and receiver points can be obtained or deployed in dense fashion, what can be done for remote, heavily forested areas to acquire high density surveys like East Siberia. In this paper we evaluate the planning and design work necessary for complex environments and propose acquisition techniques and survey designs that will make high trace density 3D acquisition possible amidst extreme surface and near surface complexities. We find that high data density survey techniques are now feasible using modern approaches for increasing channel count in the field (reduced bin spacing for improved spatial resolution) while increasing overall trace density albeit complex surface and near surface conditions.
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QRTM – Stable and Effective Anelastic Loss Compensation
Authors N. Da Silva, L. Casasanta and S. GrionSummaryWe introduce a stable and robust approach for QRTM by compensating seismic data for the effects of anelastic loss. Our approach is based on computing matching filters between attenuated and non-attenuated data in the shot domain. The filters are used to mitigate the effect of attenuation in the field data. Subsequently, the corrected data is migrated using a conventional RTM algorithm. Our approach can handle anisotropy, is not limited by using ad hoc parameters and can handle correctly the kinematics and dynamics of wave propagation in complex attenuating media. In addition, it circumvents time-reversing attenuating wave equations, which is an intrinsically unstable operation. The effectiveness and robustness of the method is shown using synthetic and field data examples where it improves imaging and gives realistic amplitudes especially in the deeper sections.
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Seismic Time-Frequency Analysis by Using an Optimized Three Parameter Wavelet Extracted by AIDNN
More LessSummarySelecting a matched wavelet to the seismic wavelet is a key issue for characterizing time-frequency features of seismic data accurately. The three-parameter wavelet (TPW) can match different seismic wavelets by adjusting three parameters. However, it is difficult to select an appropriate TPW matched well with seismic wavelets in real applications. In this study, we propose a basic wavelet selection method by using the TPW and deep learning algorithm. The proposed workflow first builds a mapping relationship between seismic wavelet and seismic data by using the alternating iterative deep neural network (AIDNN). Based on this relationship, we then estimate the seismic wavelet. Based on the estimated seismic wavelet, we can finally obtain an analytical basic wavelet by matching the TPW to the extracted wavelet by solving an optimization problem. Note that we name the TPW with optimized parameters as the optimum TPW (OTPW), and its WT is OTPWT. To demonstrate the validity and effectiveness of the proposed workflow, we apply it to synthetic traces and field data. Both synthetic and field data examples illustrate that the OTPW characterizes time-frequency features of seismic data with high resolution and is with good anti-noise property.
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Rock Physics Feasibility Study of the Lower Cretaceous Unit in the Valdemar Field, Danish North Sea
Authors K. Bredesen, M. Lorentzen, R. Rasmussen, L. Nielsen and H. YuanSummaryThe Lower Cretaceous unit in the Danish North Sea is recognized for being geologically complex and challenging to image with seismic data. We present a rock physics feasibility study, focusing on the Tuxen Formation in the Valdemar Field in the Danish North Sea. The presented work includes a pore stiffness interpretation, lithofacies classification and rock physics modelling based on well log data from BO-2X. The results indicate that methods for quantitative seismic interpretation can, in principle, be used to achieve supplementary reservoir information from seismic data, for the geological scenario given. A rock physics model is also calibrated to the Tuxen reservoir, which can be used to investigate the elastic properties and seismic response of various reservoir scenarios.
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Integrated Prediction of Gas-Bearing Volcanic Reservoirs Using Full Stack Seismic Data in Sichuan Basin of China
More LessSummaryRecently, a major breakthrough in the exploration of volcanic gas reservoirs was first achieved in Sichuan Basin, which indicates the huge volcanic rock exploration potential in this area. However, the prediction of volcanic reservoirs is very challenging because of the strong heterogeneity, the vague interior reflection structure and the low exploration level with sparse wells in this area. To reduce the exploration risk, we develop an integrated prediction strategy for the gas-bearing volcanic reservoirs using the full stack seismic data by combining the Bayesian adaptive seismic inversion and the frequency-dependent fluid mobility attribute. In the seismic inversion, an automatically adjusted prior stabilizer is derived to balance between the vertical resolution and the inversion stability according to the noise level. In the gas detection, the fluid mobility attribute is calculated by the high precision matching pursuit algorithm to directly indicate the gas reservoirs. Application in a newly discovered volcanic gas production area in Sichuan Basin shows that the integrated prediction results of gas-bearing reservoir at the borehole-side traces match well with the log interpretation result, which demonstrates the effectiveness and feasibility of this integrated method.
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3D Fault Detection Based on GCS-Net
More LessSummaryDetecting fault from seismic images is really useful for interpretation of geologic structures and stratigraphic features. With the recent developments in deep learning, this study makes it possible for efficient seismic fault detection based on convolutional neural network. In this work, we propose a general segmentation network that works on real 3D seismic data. We propose a novel network (GCS-Net) which includes a global context block (GC) and channel attention module together with spatial attention module (CS) between the encoder and decoder, instead of the U-Net based convolutional neural network. The GC block is able to capture the long-range dependencies and the CS block is utilized to further integrate local features with their global dependencies adaptively. The proposed approach was trained on a synthetic seismic data and tested by the real data. Experimental results show that our method has better performance to some extent.
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A Complete Workflow for Predicting S-Wave Velocity in Wells without Mineral Content Data
More LessSummaryShear wave velocity is the basic data for reservoir prediction and fluid detection. Therefore, an effective method to accurately predict S-wave velocity is one of the important research re-quirements. In this paper, we propose a workflow for successfully predicting S-wave velocity in tight carbonate areas. In view of the general lack of mineral content and shear wave information in logging data, we carried out the inversion of the matrix modulus firstly by a self-adapting method, and then according to the characteristics of microcrack development in tight carbonate rocks, simplifying the pore type. Through the rock physics model, the shear wave velocity in this area is predicted successfully.
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Vertical Seismic Profiling While Drilling Using Passive Monitoring Data
Authors A. Goertz, E. Bergfjord, A. Libak and S. BussatSummaryWe extract seismic-while-drilling (SWD) data from passive seismic recordings acquired with the Grane PRM array. The drill-bit pilot trace used for correlation is estimated by means of array beam forming. We observe a strong coherent signal emanating from the drill bit during times of actual drilling, when the rate of penetration (ROP) is high. For one PRM node near the wellhead, we assemble the while-drilling signals into regular depth intervals along a portion of the deviated well path. The resulting dataset is equivalent to a reverse vertical seismic profile (RVSP). We apply a check-shot VSP processing flow to extract reflected signals from below the drill bit that can be used for interpretation. We observe a good match of the RVSP corridor and corridor stack with a crossline section of the 3D seismic at Grane. This validates that passively collected seismic-while-drilling data at Grane may be utilized to look ahead of the drill bit. Using an ocean bottom cable, we can produce VSP information in real-time while drilling without the need to stop and pull the drill string for wireline deployment.
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Anisotropic Attenuation of Stratified Viscoelastic Media
More LessSummaryIntrinsic attenuation is an important parameter for reservoirs characterization due to its strong sensitivity to fluid saturation, fractures, and rock texture. Previous studies show that intrinsic attenuation in anisotropic rocks varies with propagation direction, and the attenuation anisotropy is sometimes more significant than the velocity anisotropy. The intrinsic anisotropic attenuation can be described by an attenuation matrix and its elements are the inverse of quality factors (Qij). Here, we focus on frequency-independent intrinsic attenuation and its anisotropy caused by stratified viscoelastic media. We define attenuation anisotropy parameters (AAPs) for transverse isotropic (TI) and orthorhombic attenuation. Based on Backus averaging theory, we derive a unified analytical expression of anisotropic attenuation for different anisotropic layered models. Analyzing the variation in layer-induced anisotropic attenuation assists in guiding the stratified viscoelastic reservoirs characterization.
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Combined Pre- and Post-Migration Diffraction Separation
Authors B. Lowney, H. Hoeber, E. Kaszycka and S. HouSummaryWe propose a new diffraction imaging method. Our dual method involves first applying pre-migration plane-wave destruction (PWD), followed by post-migration apex destruction and τ-p filtering to remove remaining reflection energy caused by some limitations of PWD. This approach has been tested on a real-world dataset from offshore Gabon. When comparing the new combined method to pre-migration or post-migration separation applied separately, we find a cleaner separation of diffraction and reflection energy. The obtained diffraction image has also been compared with coherency to highlight areas of uptake from diffraction imaging.
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Improved 3D Seismic Quality Increasing Trace Density Benefits and Results, Golfo San Jorge Basin, Argentina
Authors N. Cooper, Y. Herrera-Cooper, L. Vernengo and E. TrincheroSummaryIn 1997 a 3D survey was acquired in the Golfo San Jorge Basin in the center of the Argentinean Patagonia. After thorough analysis it was possible to correlate the poor data areas with intrusive bodies that occur at shallow levels and appear as overlapping lenses of irregular shape. These lenses generate diffraction points that interact with the reflections in a chaotic manner. The zones of interest lay at a significant depth below these intrusives. A new 3D was recorded in the same location as the 1997 survey. Different techniques were used to accomplish these objectives including reprocessing, wave equation modelling, data simulation, increasing trace density and statistical diversity, midpoint scatter, receiver arrays and source arrays.
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Direct Diffraction Separation by Deep Learning on Pre-Migrated Seismic Data
Authors B. Lowney, I. Lokmer, G.S. O’Brien and C. BeanSummaryDiffraction imaging is a niche imaging technique which aims to directly image discontinuities in the subsurface by separating diffractions from the rest of the wavefield and processing them independently. However, to separate diffractions is a complicated procedure due to their weak amplitudes and the overlap of energies between diffractions and the much stronger reflections. While analytical methods exist to separate diffractions, they require parameterisation, are comparatively computationally expensive, and leave a volume which contains both diffractions and noise. Here, we aim to use a Generative Adversarial Network (GAN) to automatically separate diffractions from reflections on pre-migrated seismic data without the need for parameterisation.
We have applied the GAN to two real datasets, one for validation, which comes from the same dataset used in training, and one which is used solely for prediction. This shows good results for both the validation and prediction data when compared to plane-wave destruction, an analytical separation technique, and is applied in a fraction of the time. The prediction dataset is then added to the overall training data, the network retrained and applied to the same validation data. This further improves the separation on the validation data and suggests that additional data may enhance the separation.
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Accurate Measurement of Seabed Subsidence at the Ormen Lange Field
Authors H. Ruiz, A. Seregin, O.P. Skogly, A. Libak and M. LienSummaryField-wide seafloor subsidence measurements are a mature reservoir monitoring technology, utilized in ten hydrocarbon fields in Norway. These measurements provide lateral information on pore compaction and pressure depletion in the reservoir. The survey method uses water pressure measurements at the seafloor as a starting point and reaches accuracies of 2 – 5 mm. Field cases demonstrate that the lateral distribution of subsidence can be used to identify undrained compartments and to calibrate the geomechanical model, hence providing improved interpretation of seismic time-shifts in the overburden.
Shell manages the Ormen Lange field by utilizing a combination of technologies: time-lapse gravity is used to quantify mass changes in the reservoir, providing valuable constraints for dynamic reservoir modelling; seabed subsidence is used as an indirect measurement of compaction throughout the reservoir; and 4D seismic provides the vertical resolution required to interpret these datasets in three dimensions.
In this abstract we present a solution, based on temperature-stabilization, that eliminates temperature-induced effects in subsidence surveys. We show that it provides sub-centimeter accuracy at the Ormen Lange field, with a range of depths extending for almost one kilometer. Finally, we discuss how this data is used and combined with other data types to manage the reservoir.
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Extracting Fresnel Zone from Migrated Dip-Angle Gather Using Convolutional Neural Network
More LessSummaryFresnel zones are helpful for obtaining a high signal-to-noise ratio (S/N)-migrated result. A migrated dip-angle gather provides a simple domain for estimating 2D Fresnel zones for 3D migration. We develop a deep-learning based technology to automatically estimate Fresnel zones from migrated dip-angle gathers, thus avoiding the cumbersome task of manually checking and modifying the boundaries of the Fresnel zones. A pair of 1D Fresnel zones are incorporated to represent a 2D Fresnel zone in terms of the inline and crossline dip angles, because it is difficult to directly extract 2D Fresnel zones from a 2D dip-angle gather. The proposed convolutional neural network (CNN) is established by modifying VGGNet. As picking boundaries of the Fresnel zones is a regression problem, we remove the last soft-max layer from the VGGNet. The last three convolution layers and a pooling layer are also removed, because the feature maps are small enough. To improve the contrast and definition, we enhance the features of the reflected events in the dip-angle gather. Data normalization is carried out to accelerate the training process using a simple-rescaling method before training the modified VGGNet. Field data examples demonstrate the effectiveness and efficiency of the proposed method.
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Imaging Complex Fault Structures On-shore Oman Using Optimal Transport Full Waveform Inversion
Authors O. Hermant, A. Aziz, S. Warzocha and M. Al JahdhamiSummaryBroadband high-density surveys have opened the way for the application of full-waveform inversion (FWI) on land. For these surveys, initial FWI results were promising. They demonstrated that land FWI can be an effective tool for velocity model building. However, despite these successes, difficulties remain associated with cycle skipping, and with convergence at high frequencies. Multi-dimensional Optimal Transport (OT) FWI has been shown to offer a solution for the inversion of low frequencies, with a better mitigation of the cycle skipping problem.
We present the results of a workflow, which updates with multi-dimensional OT-FWI to 16 Hz a velocity model for a land dataset from the Sultanate of Oman. The study is based on a modern full-azimuth long-offset dense broadband surface seismic survey. The geological context is a complex strike-slip fault system, causing sharp lateral velocity variations in the faulted area. Until recently, imaging beneath the faulted area was challenging due to the wavefield complexity induced by the lateral velocity variations. Previous attempts at building an accurate velocity model using ray-based tomography failed due to difficult horizon interpretation and residual move-out picking on migrated gathers. We show that using multi-dimensional OT-FWI leads to significant improvement concerning all these issues.
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