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76th EAGE Conference and Exhibition 2014
- Conference date: June 16-19, 2014
- Location: Amsterdam, Netherlands
- Published: 16 June 2014
41 - 60 of 1028 results
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Temperature Gradient Anomalies in the Buntsandstein Sandstone Reservoir, Upper Rhine Graben, Soultz, France
Authors S. Haffen, Y. Geraud, M. Diraison, C. Dezayes, D. Siffert and M.H. GarciaSummaryThe geothermal reservoir at Soultz-sous-Forêts is targeted in a granite horst bounded by subvertical normal faults. Exploration and production results tend to show that the Buntsandstein formation, made of inter-bedded sandstones and argillite in the Rhine Graben, above the granitic basement, may also have geothermal potential. Indeed, temperature gradient anomalies observed in the Buntsandstein indicate that the Buntsandstein could be exploited to produce heat or even electricity. In order to determine the fluid flow pattern within the sandstone formation, we compare two temperature gradient logs: on the one hand, the observed gradient log derived from temperatures measured along a borehole, on the other hand, a calculated one based on thermal conductivities measured on borehole cores. The observe temperatures gradients anomalies, could be explained by fluid flow patterns, thus phenomenological study has been carried out using TOUGH2 to simulate fluid flow and heat transfer for various boundary conditions. These results allow building a conceptual model (980–1400 m) of the sedimentary reservoir above the granitic basement at Soultz-sous-Forêt.
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Realistic DFN Modelling Using 3D 3C Seismic Data for the Marcellus Shale with Application to Engineering Studies
Authors S.J. Emsley, S. Chi, J. Hallin and J. RivasSummaryThe development of resource plays is moving on from drilling on a regular grid; but it is not sufficient to ‘simply’ identify a sweetspot in a resource play. It is also necessary to understand connectivity and compartmentalisation, this may be achieved through the development of a realistic fractured reservoir model. Seismic data volumes, inversion studies and rock physics provide a wealth of information covering reservoir intervals. Co-rendering of the data volumes leads to a more easily interpretable image of the subsurface and a better understanding of the reservoir. This paper discusses the construction of a realistic DFN model that was built using inputs derived from a 3D multi-component seismic dataset, seismic attributes, anisotropy information, seismic inversion results and well data. As model incorporates the seismic data deterministically the DFN can be used to guide well placement and planning, predict inter-well connectivity and can be used to forward model completions in terms of fracture generation or reactivation and micro-seismic event generation.
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Fracture and Carbonate Reservoir Characterization Using Sequential Hybrid Seismic Rock Physics, Statistic and Artificial
By D. HasanusiSummaryTiaka field is located in the Senoro-Toili block at the eastern arm of Sulawesi, Indonesia. The main hydrocarbon bearing reservoir is a lower Miocene carbonate sequences which posses a dual porosity system both matrix and fracture. This carbonate complexity is required special treatment to precisely characterize the reservoir.
In this paper, the latest technology for carbonate complex reservoir characterization using hybrid seismic rock physics, statistic and artificial neural network will be presented. This methodology enable in integrating a huge size of various data set to produce “coherence correlation” among input data and their target. The data set consist of core, electric logs, multi-attribute either pre-stack or post-stack of a 2 D seismic lines and seismic rock physics. The whole input data was trained using workflow and combined with statistic and artificial neural network to predict reservoir parameters.
This method is applied to predict the lateral lithofacies, fracture, porosity, fluid or hydrocarbon distribution. By using these approach, its can produce high accuracy on the reservoir parameter prediction. The accuracy of testing process show that predicted parameter reservoir on the average 90 percent matched reservoir parameter in the existing wells.
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Identification of Facies from Multiple Well Logs Accounting for Spatial Dependencies and Convolution Effects
Authors D.V. Lindberg, E. Rimstad and H. OmreSummaryFacies identification from multiple well logs is performed in a case study on a pair of wells from a reservoir offshore Norway. The inversion is cast in a Bayesian setting, with spatial dependencies in the facies enforced in the prior model by a Markov chain assumption and with possible convolution effects accounted for in the likelihood model. The proposed method outperforms a simpler model without these two properties in terms of correct facies classification, with more reliable predictions especially on layer thickness.
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An Innovative Approach for Formation Fluid Typing with API and GOR Assessments in Real Time from Mud Gas Data
Authors D. Merino-Garcia, G. Beda, J. Dessay, A. Nouraei and B. LovattiSummaryRepsol Sinopec Brasil has refined the operational methodology to quantitatively determine methane to pentane composition from mud gas, establishing good matches with the laboratory PVT gas data.
Deriving hydrocarbon reservoir fluid properties, from mud-gas data while drilling, is an attractive perspective. The proposed methodology includes an in-house mathematical model with:
- Two parameters (alpha and beta) to describe the composition of the hydrocarbon fluids, except those that are altered by secondary processes.
- Mud gas ratios and delineation of alpha-beta regions to predict fluid type, API and GOR in ranges adequate for operational decisions. Prediction is enhanced by tuning to regional data.
Two examples from offshore Brazil are presented as proof of concept, a gas reservoir from the “post-salt” turbiditic deposits and a rich gas condensate reservoir from the “pre-salt” carbonates. Real time evaluation of fluid typing, GOR and API is illustrated by a “post-salt” appraisal well.
This new approach has a significant impact at the exploration and appraisal drilling stages. Early fluid type identification with API and GOR assessments can be integrated into the objectives of the fluid sampling program from wireline. More important, it helps to properly design the well testing at an early operational phase.
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Carbonate Seismic Rock Physics Modeling and Hydrocarbon-detection
Authors Y.J. Zhou, X.H. Zhang, Y. Lei, H.S. Sun and Z.G. HeSummaryCarbonate reservoirs accounted for more than 50% of total reservoirs worldwide, however, the carbonate reservoir is characterized by complex structure and strong heterogeneity, seismic reservoir characterization is facing enormous challenges. This paper focuses on the dolomite reservoir of Majiagou formation in Jingbian gas field, Changqing Oilfield, the biggest oilfield in China. Through analysis of amounts of drilling, logging and testing data, the author clarify the key factors affecting the velocity of dolomite. For the first time the empirical equations of Vp, Vs and dolomite’s density, shale content (Vsh) and gas saturation were established for the study area. The sensitive factors of lithology and fluids are selected. With prestack simultaneous inversion and cross plots of sensitive factors, the most prospective area was selected and has been proved by the drilling results. Through this study, the technology of seismic characterization for dolomite has been set up.
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Integrated Reservoir Modelling Workflow for Deep Water Turbiditic Reservoirs - An Angola Case Study
Authors G.B. Straathof, C. Rigollet, F. Ferdinandi and G. SpregaSummaryAngolan deep water offshore is one of most prolific area for hydrocarbon exploration and production. The main discoveries are in high sinuosity turbiditic channels of Miocene and Oligocene age, deposited in slope valley corridors. The large amounts of sediments sourced from the African margin and the high energy level of the depositional environment create numerous discontinuities at regional and local scale, producing complex sedimentary structures ( Anka et al. 2009 ). The heterogeneities inside the reservoir impact the connected volumes and reservoir fluid path.
The paper describes a reservoir modelling workflow developed to simulate the reservoir architecture and analyse the uncertainties related to reservoir connectivity for a small oil field offshore Angola. Fluid path discontinuities above and below the corridor scale were split and managed with an innovative approach. A deterministic geological concept for the channel complex valleys was established to drive the seismic interpretation. Individual slope valley corridors mapped on the seismic provided the framework for the reservoir architecture and the facies simulation. Sub-corridor discontinuities were subsequently treated in a probabilistic way generating multiple realizations closing the data uncertainty gap. The result of this integrated workflow provides a reliable reservoir model appropriate for field development planning and reservoir management.
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Reservoir Characterization Using Converted-wave Seismic Data - Case Study from Athabasca Oil Sands
Authors C. Dumitrescu, G. Larson, F. Mayer and D. TalingaSummaryThe Lower Cretaceous McMurray Formation reservoir used in this study is located in the Athabasca basin, of the Northern Alberta, Canada. High resolution multicomponent 3D seismic data, along with core and well data were processed using the most advanced workflows in order to image the reservoir heterogeneity. These workflows include petrophysical analysis, joint PP-PS inversion and neural network analysis. Three inversions using PP and PS seismic data are analyzed and compared. The joint PP-PS inversion of the prestack seismic data produces the best estimates of P-impedance, S-Impedance and density, allowing for excellent reservoir characterization.
Neural network analysis is used to enhance the resolution of the elastic properties estimated from joint PP-PS prestack inversion, and to estimate petrophysical and engineering properties such as porosity, resistivity and saturation. In all neural network analyses the most significant seismic attributes include converted-wave information.
Some of the results are: 1. converted-wave seismic data have a major role in oil-sands reservoir characterization; 2. estimated density seismic volume shows a good separation of the two bitumen sands; 3. P-wave velocity seismic allows better mapping of the McMurray top; 4. estimated resistivity allows not only to differentiate the reservoir from the non-reservoir but also bitumen sand from water sand.
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A New Solution to Eliminate Free Surface Related Multiples in Multicomponent Streamer Recordings
Authors M. Vasmel, J.O.A. Robertsson and L. AmundsenSummaryWe present a new method for the elimination of free surface related multiples in marine seismic data. The method can be applied to datasets that contain both pressure and vertical component of particle velocity recordings. It is based on using a time domain finite difference propagator to generate equivalent data that would be recorded if the free surface above the source and receiver level were replaced by a halfspace with the properties of the water layer, so that all upgoing events radiate outwards instead of being reflected by the sea surface. The interaction with the unknown subsurface geology is taken into account through the use of exact boundary conditions along the acquisition level where we use the recorded data as Green’s functions.
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Generalization of the EPSI Primary Estimation Algorithm for Deep-towed and Slanted Cables
More LessSummaryProperly removing the ghost effect for deep-towed and slanted cables is a non-trivial task, due to the strong notch effects of such geometries. However, processing steps like surface-related multiple elimination (SRME) and the recently developed estimation of Primaries by sparse inversion (EPSI) algorithms require ghost-free data as input. Therefore, EPSI is redefined to invert directly for the primaries without the ghost, while the input data has ghost effects. In this way the deghosting process becomes part of the inversion scheme and can be optimally handled. It will be shown that it is possible to extend the EPSI algorithm for handling ghost from deep-towed and even slanted cables.
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A Method for Unified Suppression of Surface-Related Multiple and Ghosts
More LessSummarySurface-related multiple (SRM) and ghosts are challenging tasks in marine data processing. The surface-related multiple elimination (SRME) method has been proven effective in many cases. But a deghosting process must be applied in advance. The absence of ghosts makes the multiple predicted by SRME less accurate and the adaptive subtraction struggles. We propose a method for unified suppression of SRM and ghosts (USMG). The ghosting operator is used as part of the predictor instead of discarding it. In this way, both the ghosts and SRM are predicted at the same time. Moreover, the predicted multiple is more accurate because of the ghost operator. Therefore, this results in better multiple elimination. Tests on synthetic and field datasets show the feasibility of this method.
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Multilevel Acceleration Strategy for the Robust Estimation of Primaries by Sparse Inversion
Authors T.T.Y. Lin and F.J. HerrmannSummaryWe propose a method to substantially reduce the computational costs of the Robust Estimation of Primaries by Sparse Inversion algorithm, based on a multilevel inversion strategy that shifts early iterations of the method to successively coarser spatial sampling grids. This method requires no change in the core implementation of the original algorithm, and additionally only relies on trace decimation, low-pass filtering, and rudimentary interpolation techniques. We furthermore demonstrate with a synthetic seismic line significant computational speedups using this approach.
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Multiple Attenuation Using MultiFocusing Technology
Authors M. Rauch-Davies, A. Berkovitch, K. Deev and E. LandaSummaryThe removal of multiples energy on seismic data has been a major issue on many datasets worldwide. The primary advantage of MultiFocusing (MF) is the enhancement of the signal-to-noise ratio of both stacked sections and prestack data through stacking a much larger number of traces than in conventional CMP processing. We present a modification of the MF-based approach when multiples are recognized directly in the MF attribute domain. First, they are predicted according to MF wavefront parameters and then they are subtracted using an adaptive least squares method. The key elements of the proposed procedure are the MF attributes. We identify and predict the multiples in the MF attribute domain through interpretation of the RMS velocity and emergence angle panels, which are determined from the pre-stack data during the MF multidimensional analysis. We compute a multiple model based on the partial coherent summation of the original data along the predicted traveltime surfaces. For the final stage, we adaptively subtract the predicted multiples from the original data using a least squares adaptive subtraction procedure similar to SRME-type multiple attenuation methodology. We presented a multiple attenuation methodology using MF applied on a real data example.
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Shallow Reverberation Prediction Methodology with SRME
Authors S.R. Barnes, R.F. Hegge, R. van Borselen and J. OwenSummaryIt is well known that surface-related multiple elimination (SRME) breaks down when applied to shallow water datasets. The prediction is distorted at the reconstruction stage by the NMO stretch of the seabed, progressing to the loss of seabed information beyond the critical distance. Furthermore, the adaptive subtraction (multiple elimination) struggles when several orders of the predicted short period reverberation are present, within a given design window for minimization, as the predicted amplitude (and phase) between multiple orders from a single convolution of the data with itself are incorrect.
This abstract describes a novel seabed modelled SRME approach with regards to predicting simultaneously and non-iteratively both the amplitude and phase of simple and pegleg source and receiver-side sea layer reverberation correctly with minimal distortion for moderately undulating shallow seabeds.
Using a shallow water dataset from the Central North Sea, it is demonstrated that the 3D approach can replace more limited 1D T-p shot-based deterministic multiple prediction techniques to form part of a multi-model multiple prediction strategy that includes iterative SRME where appropriate.
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Water-layer Demultiple Using Separated Wavefields From Variable-depth Streamer Data
More LessSummaryWe present an approach for water-layer multiple attenuation using up-going and down-going wavefields available from pre-migration deghosting of variable-depth streamer data. After extrapolation of the separated wavefields to the seabed, the down-going wavefield is used as a multiple model which is adaptively subtracted from the up-going wavefield. The water-layer related multiples removed by this procedure are forward propagated to the variable-depth streamer datum where they are finally subtracted from the deghosted data. We illustrate the concept using a synthetic example and shows results from a variable-depth streamer dataset acquired in the North Sea.
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Surface Multiple Attenuation Developments in the Clair Field
Authors A. Dawson, S. Wolfarth, C. Leone, M. Salgadoe and R. AlexandreSummaryMultiples are a key problem over the Clair area, mainly caused by the complexity in the overburden. The paper describes a much improved combination of demultiples techniques, which have been applied to the latest Clair South West HDOBC survey. The sequence consists a top-down approach removing successive multiples with PZ summation, Wavefield Extrapolation Multiples Modeling, GSMP and TauPQ deconvolution.
Water bottom WEMM plays a key role, effectively predicting water layer multiples in a 3D sense. GSMP complements the results of the other techniques against short period multiples, but more importantly it also predicts other long period surface multiples which are cutting through at reservoir level. The results are a much improved level of multiples suppression, although some surface multiples contamination is still present, and internal multiples have not been attenuated.
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Using RTM Angle Gathers for Velocity Model Building in a Structurally Complex Area - A Real Case Study
Authors O. Hermant, S. Hassan and J.P. MontelSummaryVelocity model building for pre-stack depth migration mainly relies on ray-based tomography methods. These methods usually produce good results when the moveout (RMO) information is reliable. From the imaging side, it is now established that Reverse Time Migration (RTM) is a higher fidelity imaging algorithm compared to Kirchhoff and Beam migrations and can provide the kinematic information needed for tomographic inversion. We show in this paper a real example of using RTM 3D angle gathers for ray-based tomography. The comparison between Kirchoff migrated and RTM migrated gathers shows the uplift of RTM on focusing and signal to noise ratio which in turn improves the RMO picking. We then show that nonlinear slope tomography can improve the velocity model and lead to better imaging provided the kinematic properties of the migration algorithm used are preserved during demigration of the RMO picks.
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Diffraction Imaging for Exploration of Seafloor Massive Sulfide Deposits - Case Study Solwara 1 Site
Authors K. Tertyshnikov, R. Pevzner, A. Bóna, F. Alonaizi and B. GurevichSummaryExtraction of mineral resources on land is becoming increasingly difficult. Recent discoveries of seafloor massive sulfides (SMS), which host significant amount of mineral commodities, appear as a new potential offshore mining sector. The marine 3D seismic exploration survey was carried out over a seafloor massive sulfide deposit at Solwara 1 site in the Bismark Sea, west of New Ireland, Papua New Guinea. Despite the fact that all prospective sulfide mineralization zones are concentrated close to the seafloor, knowledge of internal deep geological structures of seabed volcanic ridges and their genesis is important for understanding of the formation of mineral deposits. The steered migration with diffractions was applied to 3D seismic volume to emphasize deep geological structures and to enhance the signal to noise ratio of the seismic images. The post-stack steered migration utilizes coherency attributes obtained by a diffraction imaging algorithm in 3D to weight or steer the main Kirchhoff summation. The application of the steered migration to the investigation of the modern subduction zone at the Solwara 1 mine enhanced the signal to noise ratio of the final migrated images and helped to understand the formation mechanisms of seabed deposits in the region by exploring the deep structures.
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Subsalt Pore Pressure and Imaging Using Rock Physics Guided Velocity Modelling
Authors Y. Liu, D. Bhaskar and N.C. DuttaSummaryEarth models solely based on tomography may be non-unique, especially in presence of anisotropy or subsalt where incidence angles are small. The latter is a major problem for subsalt pore pressure prediction. In the method proposed here we constrain the subsalt tomography using geology in conjunction with thermal history modelling and rock physics principles. This is referred to as rock physics guided velocity modelling for migration and pore pressure prediction. A novel feature of this technology is to use predicted pore pressure as a guide to improve the quality of the Earth model. Thus, we produce a velocity model that not only flattens the CIP gathers, but also limits the velocity field to its physically and geologically plausible range without well control. This yields both a better image and pore pressure prediction below salt.
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The Seismic Response to Strong Vertical Velocity Change
By I.F. JonesSummaryConventional seismic data processing, whether it be pre-stack data conditioning or migration, is designed with the theory of P-wave reflected energy in-mind, for travel paths involving only a single reflection. Any energy propagating with other modes or travel paths will not be dealt with appropriately during conventional seismic data processing. It is primarily for this reason that we spend so much time preconditioning seismic data, so as to meet the assumptions of the subsequent migration. In this study, looking at shallow-water marine data from high velocity-contrast environments (such as found with basalt or carbonates), I assess the behaviour of some other classes seismic energy, when subjected to conventional processing, so as to better understand the anomalous events appearing in migrated CRP gathers and images, due to contamination of the data with remnant refraction and mode-converted energy.
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