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82nd EAGE Annual Conference & Exhibition
- Conference date: October 18-21, 2021
- Location: Amsterdam, The Netherlands
- Published: 18 October 2021
51 - 100 of 1137 results
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VSP Study Using DAS at the Medipolis Geothermal Well and Implication of a Deep High-Vp/Vs Zone
Authors J. Kasahara, Y. Hasada, H. Kuzume, H. Mikada and Y. FujiseSummaryFollowing our first seismic study at the Medipolis geothermal field in southwestern Japan in 2018, we conducted a second seismic study at the same geothermal field in 2019. We installed an optical-fiber system for distributed temperature sensor (DTS) and distributed acoustic sensor (DAS) measurements. We deployed the optical-fiber system at a 1,545-m depth in the IK-4 borehole. The temperature was measured to be 272.8 °C at a 920-m depth and 152.8 °C at a 1,530-m depth. We operated a MiniVib seismic source at five locations and performed a frequency sweep of 10–75 Hz 480 times each day, for seven days. We cross-correlated the seismic records and the source signature and stacked the correlated data to enhance the S/N. Stacking for 480 or 960 times considerably improved the arrival waveforms. Based on an analysis of DAS data, we constructed the 2D seismic profile. We estimated three major hydrothermal layers, at depths of 800–1,000 m, 1,300–1,600 m, and 3,600 m. The zone around 3,600 m suggests a high Vp/Vs value and the possible presence of a fluid layer.
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Experimental Study on the Effect of Supercritical CO2 on Shaly Caprocks
More LessSummaryPetrophysical properties such as porosity and pore size distribution are critical parameters in seal integrity of the caprock. The effect of interactions between CO2, brine, and minerals constituting the caprock, have a significant influence on the effectiveness of the caprock sealing properties. Alteration of caprock integrity leads to environmental problems and bringing into question the effectiveness of the program altogether. In this study, shale samples were exposed to supercritical CO2 (scCO2) at in-situ pressure, temperature, and salinity condition, representative of a CO2 storage operation in Southwest Hub, Western Australia. Petrophysical properties of the samples are analysed with several methods to track the changes after exposure of samples to CO2. With this approach, we show that in the context of tight samples, the alteration of caprock minerals could result in either porosity enhancement or diminishment. Pore size distribution curves form nuclear magnetic resonance (NMR), low-pressure nitrogen adsorption (LPNA), and mercury injection capillary pressure (MICP) tests indicate an increase in pore volume, except for relatively tighter, clay-rich samples.
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Converted Wave Traveltime Approximation in Elastic Orthorhombic Media
More LessSummaryIn order to approximate the traveltime in an elastic orthorhombic (ORT) medium for converted waves, we define an explicit rational-form approximation for the traveltime of the converted PS1, PS2 and S1S2 waves. For the simplification purpose, The Taylor-series approximation is applied in the corresponding vertical slowness for three pure-wave modes. By using the effective model parameters for PS1, PS2 and S1S2 waves, the coefficients in the converted-wave traveltime approximation can be represented by the anisotropy parameters defined in the elastic ORT model. The accuracy in the converted-wave traveltime for three ORT models is illustrated in numerical examples. One can see from the results that for converted PS1 and PS2 waves, the proposed rational-form approximation is very accurate regardless of the tested ORT model. For a converted S1S2 wave, due to the existence of cusps, triplications, and shear singularities, the error is relatively larger compared with PS waves.
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Traveltime and Relative Geometrical Spreading Approximation in Elastic Orthorhombic Medium
More LessSummaryWe define the Rational Form (RF) approximations for P-wave traveltime and relative geometrical spreading in elastic ORT model. To facilitate the coefficients derivation in these approximation forms, the Taylor series (expansion in offsets) in the vertical P-wave slowness measured at zero-offset is applied. The same approximation forms computed in the acoustic ORT model are also derived for the comparison. In the numerical tests, three ORT models with the parameters obtained from the real data are used to test the accuracy of each approximation. The numerical examples yield the results that, apart from the error along the y-axis in the ORT model 2 for the relative geometrical spreading, the RF approximations are all very accurate for all tested models in both traveltime and relative geometrical spreading that can be performed for the practical use.
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On-Axis Triplications in Elastic Orthorhombic Media
More LessSummaryWe derive the second-order coefficients (principal curvature) of the slowness surface for two S waves in the vicinity of three symmetry axes and define the elliptic form function to examine the existence of the on-axis triplication in ORT model. The existence of the on-axis triplication is found by the sign of the defined curvature coefficients. An ORT model is defined in the numerical examples to analyze the behavior of the on-axis triplication. The plots of the group velocity surface in the vicinity of three symmetry axes are shown for the ORT model where different shapes: convex or the saddle-shaped (concave along one direction and convex along with another) indicates the existence of the on-axis triplication.
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Game-Changing AI for Faster and Better Well Trajectory Planning Decisions (An Example Using the Volve Dataset)
Authors N. Dolle, T. Savels, G.C.A.M. Reijnen-Mooij, J.J. Corcutt, O.R. Hansen and E. LandreSummaryWell trajectory planning is a high-stake and complex multi-disciplinary work activity for Oil & Gas operators. The work involves experts from geoscience, reservoir engineering, drilling, completions and facilities. Each are using specialist software to evaluate and define reservoir targets, subsurface hazards and engineering constraints. “Likes” and “dislikes” of trajectory options are expressed in different terms by the various disciplines. This often leads to an iterative and time-consuming process, influenced by human bias. Time quickly becomes a limiting factor, with a business risk of unrealized value due to incomplete understanding of the full option space and associated uncertainties, risks and rewards.
To mitigate the above challenges, we have developed a collaborative game-based approach to well trajectory planning supported by Artificial Intelligence (AI). This approach has been tested using Equinor’s open source Volve dataset, which demonstrates the potential to significantly reduce cycle time and improve decision quality.
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Multidimensional Factorial Kriging for Prestack Filtering
Authors T. Demongin and C. MagneronSummaryThe presence of stationary and non-stationary noise in prestack seismic data, despite reprocessing improvements, can be tackled by an innovative Factorial Kriging technique. Indeed, the data can be considered in a 4D space, counting the offset value. A multidimensional filter, using a 4D variogram model, is then resolved with the same system as in the case of usual 3D Factorial Kriging.
A NMO corrected raw migration gathers case study is presented, with results and interpretation. It appears in the end that noise observed on gathers and offset planes is removed and the data shows an improved signal to noise ratio.
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Working around the Corner Problem in Numerically Exact Non-Reflecting Boundary Conditions for the Wave Equation
By W. MulderSummaryRecently introduced non-reflecting boundary conditions are numerically exact: the solution on a given domain is the same as a subset of one on an enlarged domain where boundary reflections do not have time to reach the original domain. In 1D with second- or higher-order finite differences, a recurrence relation based on translation invariance provides the boundary conditions. In 2D or 3D, a recurrence relation was only found for a non-reflecting boundary on one or two opposing sides of the domain and zero Dirichlet or Neumann boundaries elsewhere. Otherwise, corners cause translation invariance to be lost.
The proposed workaround restores translation invariance with classic, approximately non-reflecting boundary conditions on the other sides. As a proof of principle, the method is applied to the 2-D constant-density acoustic wave equation, discretized on a rectangular domain with a second-order finite-difference scheme, first-order Enquist-Majda boundary conditions as approximate ones, and numerically exact boundary conditions in the horizontal direction. The method is computationally costly but has the advantage that it can be reused on a sequence of problems as long as the time step and the sound speed values next to the boundary are kept fixed.
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Gramian Constraints in Electromagnetic Multi-Physics Joint Inversion
More LessSummaryJoint inversion of multi-physics is used to minimize the non-uniqueness associated with under-determined geophysical problem by some constraints. The Gramian stabilizing constraint has been used to enforce the linear correlation between the resistivity models from the frequency and time-domain airborne electromagnetic (AEM) data. The Gramian is the dot product of the two resistivity models which constrains the nonlinear least square optimization towards more reliable interpretation even in the presence of noise. Both synthetic and field data demonstrations give satisfactory results.
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Analysis of Thin Sand Recognition Using Supervised Multiattribute Classification Based on ANNs
More LessSummaryThe objectives of this work are to identify heterogeneous thin sands via machine learning (artificial neural network) and evaluate the impact of tuning thickness on the recognition. The thin sands within the study interval mainly developed in a complex fluvial to shallow marine environment. Multiattribute classification using supervised Artificial Neural Networks (ANNs) is employed to predict the distribution of these thin sands within six subintervals and the role of tuning thickness in the prediction is evaluated quantitatively.
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The Performance of Viscoelastic Surfactant-Polymer Flood in Heavy-Oil Carbonate Reservoir — Simulation Study
Authors A. Zaitoun, M. Al-Foudari, K. Zeidani, S. Al-Otaibi, A. Al-Ghadhouri, G. Omonte Rossi, J. Bouillot and A. ZaitounSummaryThis paper describes the simulations performed to evaluate different scenarios of water flood, polymer flood and Viscoelastic Surfactant (VES) combined with polymer blend in a Middle Eastern carbonate reservoir. Compared to classical Alkaline-Surfactant-Polymer (ASP) EOR technology, VES-Polymer does not require heavy water processing and is thus more robust and easier to deploy on the field. The simulation study used coreflood data set obtained by a laboratory study presented in another paper and aimed at optimizing a field pilot.
The simulation was conducted with a pattern of three parallel horizontal wells; one central injector and two lateral producers. A well length of 2000 meters and spacing of 100 meters was found to be the best configuration for the pilot. For waterflood, the unfavorable mobility ratio induced early water channeling. Due to more favorable mobility ratio, polymer flood shows better performances in terms of incremental oil production and VES-Polymer flood further increases the oil production compared to polymer flood due to combination of IFT reduction and increase in sweep efficiency.
Both polymer flood and VES-Polymer flood can thus be considered as valuable EOR options in this type of reservoir conditions which have not been considered so far
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Structural and Depositional Features Controlling Permeability on Carbonate Platforms
Authors R. Loza Espejel and T.M. AlvesSummaryNaturally fractured reservoirs present a challenge when determining the permeability associated with different types and sizes of fractures. Permeability in these reservoirs depends on the heterogeneity and connectivity of open fractures; although depositional and diagenetic features also play an important role. In this study, a multi-scale analysis of the Cariatiz Fringing Reef Unit in SE Spain is completed based on outcrop and LiDAR data. Seven different features were found to influence the permeability of the Cariatiz Fringing Reef Unit. Structural features comprise: (i) joints, (ii) veins, (iii) vertical fractures, (iv) fracture swarms, and (v) karsts. Two types of depositional features were also recognised at outcrop:(vi) vertical Porites and (vii) pseudo-bedding surfaces. All contribute to increased permeability, apart from calcite-filled veins that create barriers to fluid flow. The results of this study highlight the complexity of carbonate systems and the need to collect data at different scales of analysis to decrease uncertainties in reservoir models. The approach in this work is valid in hydrocarbon exploration and production, geothermal reservoir characterisation, environmental studies and carbon sequestration projects.
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Deep-Marine Hyperpycnal Sandstones and Implications for Exceptional Reservoir Quality Preservation
Authors J. Cater, T. Gould and B. UrsinusSummaryDeep marine hyperpycnal sandstones form prolific hydrocarbon reservoirs but remain poorly understood despite over 40 years of research. Predicting their geometry, composition and reservoir quality requires a thorough knowledge of the processes that formed them and the effects of diagenesis in the presence of brackish depositional pore waters. Dissolution of unstable grains (e.g. feldspars and volcanic material) and replacement by kaolinite and chlorite/smectite occurs more readily in the presence of brackish, acidic pore fluids. This is enhanced locally as compaction drives fluids through the aquifer. Pore lining chlorite cements can help to prevent chemical compaction of quartz grains and impede later quartz overgrowths, helping to preserve reservoir quality at depth. Commonly in hyperpycnal deposits, remnant pore fluids are of low salinity, resulting in anomalous low salinity DST results (e.g. Agat, NOCS). The salinity of the pore fluids soon after deposition can be quantified by measuring the isotopic composition of early carbonate cements, which may form strata bound or nodular baffles to flow within the aquifer. The influence and mobility of low salinity pore fluids during the early diagenesis of deep marine hyperpycnal deposits is a key subject for future research.
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Lithology Identification Based on Hidden Markov Model and Random Forest
More LessSummaryBy combining the hidden Markov model (HMM) and random forest (RF), a new approach is proposed for lithology identification. To extract more useful information from elastic parameters, the HMM is used to provide a new hidden feature. The hidden feature reveals the inner relationship of elastic parameters and this is important for machine learning. With the new hidden feature and elastic parameters, RF is adopted for lithology prediction. To guarantee the quality of the hidden feature, it is updated in a loop iteration. Both synthetic data and field data tests demonstrate that the proposed approach can improve prediction results.
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Use of Elastic Forward Modeling to Remove Complex Coherent Noises
Authors J. Tang, C. Peng, M. O’Briain and C. ShihSummaryIn the deep-water Campeche Bay area of the southern Gulf of Mexico, there are many complex shallow salt bodies and carbonate rafts that generate a significant amount of coherent noise energies, collectively for all non-primary reflection energies, as a result of the high impedance contrast between these bodies and the surrounding sediments. These noise energies include surface-related salt-diffracted multiples, interbed/internal multiples, bounces between salt bodies, and other types of prismatic waves as well as converted shear waves. These coherent noises cause difficulties in interpreting base of salt and subsalt seismic events. Identifying and removing them is crucial for optimal seismic imaging of subsalt targets.
We propose a method to model these noises using a geological imaging model and elastic finite-difference forward modeling. The method requires that the shallow part of the geological imaging model be accurate. We first compute elastic synthetic data using the model. Then, we migrate the synthetic data to generate a noise model in the image domain and use this noise model to pattern-match with another image volume migrated using field data. In this way, we can identify noises in the field data and remove them adaptively to obtain a cleaner image of the recorded reflectivity.
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Performance Evaluation of Machine Learning Algorithms in Predicting Dew Point Pressure of Gas Condensate Reservoirs
Authors P. Ikpeka, J. Ugwu, P. Russell and G. PillaiSummaryAccurate knowledge of the dew point pressure for a gas condensate reservoir is necessary for the design of a field development plan and timing for optimization of mitigation operations for resources management. This study explores the use of machine learning models in predicting the dew point pressure of gas condensate reservoirs. 535 experimental dew point pressure data-points with max temperature and pressure of 304F and 10500psi were used for this analysis. First, multiple linear regression (MLR) was used as a benchmark for comparing the performance of the machine learning models. Neural Networks (NN) [optimized for the number of neurons and hidden layers], Support Vector Machine (SVM) [using radial basis function kernel] and Decision Tree [Gradient boost Method (GBM) and XG Boost (XGB)] algorithms were then used in predicting the dew point pressure using gas composition, specific gravity, the molecular weight of the heavier component and compressibility factor as input parameters. The performances of these algorithms were analyzed using root mean square error (RMSE), absolute average relative deviation percentage (AARD %) and coefficient of determination (R2). This work concludes that for large data sets neural network is preferred but for smaller data sizes, SVM shows better performance
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Enhancing Massive Land 3D Seismic Data Using Nonlinear Beamforming: Performance, Quality and Practical Trade-Offs
Authors I. Silvestrov, A. Bakulin, D. Nekluydov, K. Gadylshin and M. ProtasovSummaryModern land seismic data are typically acquired using high spatial trace density but single sensors or small source and receiver arrays. These datasets are challenging to process due to their massive size and rather low signal-to-noise ratio caused by scattered near surface noise. Prestack data enhancement becomes a critical step in processing flow. Nonlinear beamforming was proven very powerful for 3D land data. It requires computationally costly estimations of local coherency on dense spatial/temporal grids in 3D prestack data cubes and poses inevitable trade-off between performance of the algorithm and quality of the obtained results. In this work, we study different optimization schemes and discuss practical details required for applications of the algorithm to modern 3D land datasets with hundreds of terabytes of data.
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Improved Ooil Recovery by Low Salinity Water Injection Simulation
By J. TrivediSummaryPrimary and secondary oil recovery techniques together can produce less than half of the original oil in place due to some restricting phenomena such as rock heterogeneity, capillary, and mobility ratio problems during these first two stages in oil reservoirs.( Kamranfar and Jamialahmadi 2014 ; Lei et al. 2016 ). The overall objective of implementation of any chemical EOR method including alkaline, surfactant, and polymer flooding is to decrease the residual oil saturation left within reservoir rock porous media after primary and secondary productions. Recently, LSWI (low salinity water injection) is one of the emerging IOR techniques for wettability alteration in both sandstone and carbonate reservoirs.
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Deep Learning for Anisotropy Parameters Estimation in Oil/Gas Fractured Reservoirs
Authors G. Sabinin, T. Chichinina and V. TulchinskySummaryWe study the applicability of Deep Learning in solving the problem of estimating the fractured medium parameters, represented as anisotropy parameters of a transversely isotropic model (HTI), using synthetic seismic data. Normal and tangential weaknesses of fractures ∆_N and ∆_T, the Thomsen anisotropy parameters ε, δ, γ, the crack density and the aspect ratio (crack opening) are considered. We develop a neural network model for solving this problem. Trained on synthetic seismograms, it provides quite accurate results. The effectiveness of Deep Learning for the inverse problem is demonstrated. The prospects for the development of this method for more complex rock-physics models are outlined.
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Prestack Data Enhancement with Phase Substitution and Phase Corrections Guided by Local Multidimensional Stacking
Authors A. Bakulin, D. Neklyudov and I. SilvestrovSummaryWe revisit enhancement with local stacking in the context of seismic data corrupted by near surface scattering. We discover that phase spectra derived from local stacking contains critical information that could be used as direct estimate of signal phase (phase substitution method) or as a guide (phase corrections method) to correct frequency-dependent distortions obstructing prestack data. Combining corrected phase with original amplitude spectrum, we arrive at much better estimate of enhanced data compared to conventional multi-dimensional local stacking. Specifically, we eliminate loss of higher frequencies and preserve original amplitudes, while making originally invisible reflections to become discernable and coherent for further processing. While we only present example of two possible methods, this discovery paves the way to plethora of new approaches finally enabling removing corrupting effects of complex scattering near surface beyond conventional surface-consistent processing.
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(When) Do Earthquakes Respect Traffic Lights?
Authors S. Baisch, P. Carstens, R. Vörös and K. WittmannSummaryTraffic light systems (TLSs) for limiting the strength of induced seismicity are used in different energy technologies. We use physics-based numerical models for investigating under which circumstances TLSs may not provide a robust mitigation measure. For seismicity induced by fluid injection, TLS efficiency can be limited by trailing effects caused by post-injection pressure diffusion and stress concentrations at the periphery of previous seismic activity. Seismicity caused by gas production exhibits a ‘characteristic earthquake’ pattern where earthquakes with similar (maximum) magnitude occur in the course of reservoir depletion. The characteristic earthquakes reflect repeated slip of the same reservoir fault patches. The maximum earthquake magnitude of a sequence can occur without precursors. Although trailing effects do not occur in an idealized reservoir with infinite conductivity, the lack of precursory seismicity limits the robustness of a TLS.
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Moving Toward Direct DNN-Based Enhancement of 3D Pre-Stack Seismic Data
Authors K. Gadylshin, A. Bakulin and I. SilvestrovSummaryPre-stack data enhancement with multidimensional stacking is indispensable part of modern data processing that very compute-intensive since multiple wavefront attributes need to be estimated on dense spatial/temporal grid. At the core of this demand are conventional local or global optimization techniques. We propose two alternative approaches based of artificial intelligence that can greatly reduce computational effort of estimation stage. First approach performs traditional computations on sparser grid and inpaints to dense grid using deep neural network (DNN) with partial convolution layers. Second approach is direct DNN-based attributes estimation from the pre-stack seismic data itself. Both methods incorporate multiparameter attributes by encoding them into RGB-images. On synthetic and real 3D data examples, we demonstrate, that application of these methods for seismic data enhancement using nonlinear beamforming can greatly speed up the computational time while maintaining similar quality of output data.
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Blended Acquisition with Temporally Signatured/Modulated and Spatially Dispersed Source Array: Productivity Enhancement in a Pilot Survey
Authors T. Ishiyama and T. WeiSummaryRecently, we established a blended-acquisition method: temporally signatured and/or modulated and spatially dispersed source array, namely S-/M-DSA, that jointly uses various signaturing and/or modulation in the time dimension and dispersed source array in the space dimension. We have acquired the first pilot survey with S-/M-DSA onshore Abu Dhabi. In this paper, we introduce this pilot survey and the resulting acquisition productivity enhancement in the time dimension. Furthermore, we discuss how this method could enhance the acquisition productivity in the space dimension as well. These show that S-/M-DSA significantly enhances the acquisition productivity compared to conventional blending methods.
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Mixed Phase Seismic Wavelet Estimation using the Bispectrum
By M. BekaraSummaryThe ability to estimate a mixed phase wavelet is a useful tool for processing and quality control in seismic imaging. The wavelet is estimated using higher order statistics of the data. In practice, these methods tend to show some instability issues when the wavelet length is increased. To improve the stability of the solution, this abstract proposes a new formulation of the wavelet estimation problem that constrains the solution to be a finite duration, phase-only compensation applied to a known base wavelet. The proposed solution works in the frequency domain and consists of three steps. First, the bispectrum of the data is deconvolved using the bispectrum of the base wavelet to increase its bandwidth. This helps to improve the sensitivity of third order statistics to phase information. Then, a phase-only wavelet is estimated from the deconvolved bispectrum using an iterative least-squares approach without phase unwrapping. Finally, the estimated phase-only wavelet is conditioned using a projection onto convex sets type algorithm to enforce the constraint of the finite time duration giving the user a control on the amount of phase deviation from the base wavelet. Test examples on synthetic and real data both show reliable results with robustness to noise contamination.
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Least-Squares Kirchhoff Psdm with a Local Based Inversion Approach and Compensation for Limitations in Modeling.
Authors Ø. Korsmo, S. Crawley, C. Zhou, S. Lee, E. Klochikhina and N. CheminguiSummaryReliable seismic amplitudes are crucial for the estimation of rock properties. In conventional depth imaging, amplitudes and resolution will be influence by propagation effects in the imaging model. These limitations origin from the formulation of the migration operator, implemented as the adjoint rather than the inverse of modeling. Least-squares migration (LSM) tries to eliminate these effects and resolve the real reflectivity model.
In this study, we make use of a newly developed local calibrated image-domain Kirchhoff least-squares migration to deconvolve the system response from the depth migrated gathers. We demonstrate how the inversion de-blurs the image and adjusts the prestack amplitude response, following better the expected response from well synthetic. The method is demonstrated on a North Sea dataset from the Viking Graben area, covering the Verdandi/Lille Prinsen discovery.
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Seismicity-Permeability Coupling in the Breaching and Sealing of Reservoirs and Caprocks
Authors D. Elsworth, Y. Fang, K. Im, C. Wang, T. Ishibashi, Y. Jia, E.C. Yildirim and F. ZhangSummaryThe presence of pre-existing faults and fractures in the upper crust contribute to induced seismicity as a result of fluid injection, in hydraulic fracturing, deep storage of CO2, and stimulation of EGS reservoirs. In all of these, either maintaining the low permeability and integrity of caprocks or in controlling the growth of permeability in initially very-low-permeability shales and geothermal reservoirs are key desires. We explore styles of permeability evolution using both experimental and computational methods to explore how fracture permeability changes in response to fracture/fault reactivation and investigate the roles of (1) mineralogy and (2) fracture roughness in conditioning response; together with (3) intrinsic controls of healing on the earthquake cycle and permeability evolution.
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A Perfectly Matched Layer Technique for the Lattice Spring Model
More LessSummaryThe lattice spring model (LSM) combined with the velocity Verlet algorithm is a newly developed scheme for modeling elastic wave propagation in solid media. Unlike conventional wave equation based schemes, LSM is established on the basis of micro-mechanics of the subsurface media, which enjoys better dynamic characteristics of elastic systems. But LSM is still suffering the boundary reflections and little work has been reported on this topic. The focus of the present study was to develop a special form of absorbing boundary condition based on the perfectly matched layer (PML) concept for LSM. The PML formulation is tested using a homogeneous model and the Marmousi model. The perfectly matched layer concept appears to be very well suited for LSM.
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Design of Non-Replicated Acquisition Geometries for Time-Lapse Measurements
Authors G. Blacquiere and G. BlacquiereSummaryTime-lapse, or 4D seismic is capable of satisfying the continuously increasing demand for high-quality subsurface images to reveal both static and dynamic elements during the field development. However, in practice, challenges of pursuing this strategy lie in different perspectives related to budgetary, operational and regulatory constraints. Seismic surveys, performed in a compressed manner in time and/or space, can provide high-quality seismic datasets in a cost-effective and productive manner. The processing of data acquired in this way usually requires decompression, e.g., deblending and data reconstruction. The decompression performance is of fundamental importance in determining the success of compressed measurements. Our decompression approach deals jointly with deblending and data reconstruction via a sparse inversion, coupled with constraints on causality and coherency. Additionally, we carry out the inversion simultaneously for all available vintages, sharing static information between them while extracting the dynamic changes. We use this inversion as the kernel of a survey-design scheme. We use artificial intelligence (convolutional neural network) to speed up the computations. In our experiment, using time-lapse data from the Troll field, the improvement of designing the acquisition geometry combined with the simultaneous inversion of all available vintages was 6 dB.
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Application of Stochastic Method for Geomechanical Parameters under Uncertainty Quantification to Design Mud Window
Authors M.A. Ebrahimi, M.J. Ameri and M. AhmadiSummaryA novel methodology is developed to design a reliable safe mud window based on most updated geometrical uncertainty distribution. The developed approach allows to estimate the uncertainty ranges for geometrical parameters and their dependent parameters such as collapse pressure and fracture pressure. A trustable mud window design based on posterior probability reduces the risks of wellbore stability problems and less kick.
In this research, the Markov chain Monte Carlo simulation used to quantify the geomechanical uncertainties in order to make it more clear and trustable.
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Seismic Quality Factor Estimation with a Simulated Annealing Approach: A Practical Example of the Sichuan Basin
More LessSummaryFluid movement and grain boundary friction are the two main factors responsible for the anelastic attenuation of seismic data. The quality factor Q quantifies the degree of anelastic attenuation and is commonly used in assisting the identification of gas reservoirs. We propose to employ the seismic reflections at near offset as referred seismic signals in the quality factor computation while the seismic reflections at medium and far offsets are regarded as target seismic signals. We then employ simulated annealing to simultaneously obtain the quality factor values of the targeted seismic signals. The proposed method is applied to both synthetic and real seismic data to demonstrate the validity and effectiveness. The application of SiChuan field data demonstrates that the estimated Q values using our method can be used as direct indicator the for gas reservoir.
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Multicomponent 3D-3C Data Acquisition and Processing in the Bandurria Norte Concession, Neuquén Basin, Argentina
More LessSummaryHydraulic well stimulation requires knowledge of rock mechanical parameters to reduce uncertainty attached to development of shale oil prospects. Multicomponent 3D-3C seismic data provide more reliable estimation of rock physical parameters needed for fracture stimulation in low permeability unconventional reservoirs. The design and processing of a special 3D-3C seismic survey in the Bandurria Norte concession is illustrated, whereby the Jurassic/Cretaceous Vaca Muerta Formation interval is the main target.
Seismic characterization of unconventional reservoirs necessitates: 1) high resolution input data with a high trace-to-trace correlation, 2) high signal-to-noise ratio, 3) reliable amplitudes and 4) preserved post-migration azimuthal information. Multicomponent seismics make analysis of seismic anisotropy and shear wave splitting possible. The PP-PS joint inversion scheme generates more accurate elastic properties (e.g. Young’s modulus). For these reasons, a static cable-less acquisition spread of 600 three-component (3C) receivers was laid out during the standard P-wave seismic acquisition in the Bandurria Norte Block. The multicomponent data was successfully processed and interpreted. Estimation of shear wave splitting effects improves the velocities with a positive impact on the PreSTM imaging. Directional dependency of the seismic velocities is thought related to fracture distribution and local stress regime.
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What is the Benefits of Carbonated Water Injection in Heavy Oil Reservoirs: A Case Study
Authors M. Shokriafra, H. Norouzi, B. Rostami and P. AbolhosseiniSummaryAdvantage of CWI over WI and CO2 injection for an Iranian heavy oil reservoir, is studied through core flooding experiments. Five different experiments were conducted in different wettability states using secondary and tertiary injection scenarios. The results showed that CWI is more beneficial than WI and CO2 injection. Higher sweep efficiency, more stable front, CO2 diffusion to oil and subsequent oil viscosity reduction and swelling are the reasons for better CWI performance. Moreover, due to the lower sweep efficiency of WI and low resistance channels created along the flow axis, tertiary CWI is not capable to recover all the bypassed oil, so its recovery is less than secondary CWI. The results of aged experiments indicated that by shifting wettability toward mixed wet, CWI performance decreased in both WI and secondary CWI. In mixed wet wettability several pores which were accessible for injection fluid in clean sand, are not reachable in aged sand anymore which accelerated injection fluid breakthrough and decreased ultimate recovery. Besides, it was observed that the proportion of recovery after breakthrough to the total recovery was increased for SCWI while decreased for WI, this is attributed to the acidic nature of carbonated water and consequent wettability alteration.
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A Multi-Axial Perfectly Matched Layer for Finite-Element Time-Domain Simulation of Elastic Wave Propagation
More LessSummaryWe develop a novel M-PML absorbing boundary condition for the second-order finite-element elastic wavefield simulation. We first derive the M-PML formulation and then incorporate the M-PML into the second-order wave formulation in the time domain with fewer split terms to reduce memory requirement and consequentially improve the computational efficiency. Numerical wavefield simulations are carried out to demonstrate the stability and efficiency of the proposed M-PML. The proposed algorithm can also be extended to 3D anisotropic elastic simulation of wave propagation with reasonable efforts.
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A Novel Nonlinear Joint AVA Inversion Method for Russell Fluid Factor
More LessSummaryFluid factor, as an important characterization parameter for reservoir fluid identification, is mainly estimated by the inversion methods based on the linear approximations of Zoeppritz equations. For complex hydrocarbon reservoirs, the calculation accuracy of the linear approximate formulas is low, which greatly limits the estimation accuracy of the fluid factor. To solve this problem, a nonlinear fluid factor inversion method directly based on the Zoeppritz equations is presented in this abstract. Firstly, based on poroelasticity theory, we performed several substitutions to convert the Zoeppritz equations from the classical form to a new form containing the chosen fluid factor, shear modulus and density (FMR). Then, the objective function was constructed using the new equations in a Bayesian framework. The Cauchy and Gaussian distributions were used for a priori distribution and the likelihood function, respectively. Lastly, the nonlinear objective function was solved by using the Gauss-Newton method. Both synthetic and field data show that the proposed method can stably estimate the fluid factor with high accuracy, and the accuracy is higher than that of the method based on Russell approximate formula.
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Nonlinear AVA Inversion Based on Bayesian Theory for VTI Media
More LessSummaryFor shale reservoirs with VTI anisotropy characteristic, the inversion methods based on linear approximate formulas are commonly used to estimate the elastic parameters and anisotropy parameters. However, the calculation accuracy of linear formulas is low, which limits the estimation accuracy of these parameters. In fact, the linear approximation formulas are made up of isotropic and anisotropic terms. Numerical experiments show that if we use the exact Zoeppritz equations to replace the isotropic term in these formulas, the calculation accuracy of reflection coefficients can be improved. This can reduce the influence of the calculation error introduced by the forward operator on the inversion result. Therefore, in order to improve the estimation accuracy of reservoir parameters, we constructed a Bayesian nonlinear inversion objective function based on the combined equation obtained by substitution. In addition, the differentiable Laplace distribution blockiness constraint term was also added to the Cauchy background prior model to further improve the vertical resolution of inversion results. Synthetic data test shows that the proposed method can not only inverts Thomsen anisotropy parameters stably, but also accurately estimates the vertical P- and S- wave velocities and density, which demonstrates the effectiveness of this method.
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Ambient Noise Reverse Time Migration Based on Velocity Flood for Fault Imaging
More LessSummaryWe propose a novel ambient noise Transmitted Surface Wave Reverse Time Migration (TSW-RTM) method to image interfaces of fault zones where the crystalline basement rocks truncate against the surrounding sediments. The source and receiver wavefields are propagated in the sediment flood velocity and crystalline flood velocity, respectively. The migrated image is then obtained by applying the zero-lag cross-correlation imaging condition to the forward and backward wavefields. The synthetic test demonstrates that the transmitted surface wave can provide sufficient information to form correct images at the fault surface. We then apply the proposed TSW-RTM method to image a major fault of Tanlu fault Zone near Chao Lake in eastern China, using the surface wave retrieved from the ambient noise data. Compared with the conventional ambient noise tomography method, our method provides a better imaging result with much higher resolution and certainty where both the interface position and dipping angle of fault are well consistent with the previous study. This novel ambient noise imaging method enables us to image the fault interfaces without a priori information of the fault position, which is especially useful in the study areas that are less illuminated by seismic surveys or earthquake events.
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Elastic Least-Squares Reverse Time Migration in the Rugged Seabed Structure
More LessSummaryThe marine deep water is rich in oil and gas resources. However, the severe rugged seabed structure brings great difficulties to seismic imaging in the marine environment. To accurately image the target layer under the rugged seabed interface, an elastic least-squares reverse time migration (LSRTM) in the rugged seabed structure is proposed. This method is based on a coupled equation method, which uses the acoustic wave equations in seawater and the elastic wave equations in the underlying elastic medium. The pressure and the stress are transmitted steadily and continuously by using the acoustic-elastic control equation at the seabed interface. To overcome the influence of the rugged seabed interface, the acoustic-elastic model is meshed into non-uniform curvilinear grids, and the corresponding mapping technique is used to transform the model with the rugged seabed interface to a horizontal one in the curvilinear coordinate system through the coordinate transformation. Therefore, in this paper, we overcome the limitations of the traditional finite difference method in imaging the rugged seabed structure environment caused by its regular rectangular grid generation, and proposed the LSRTM method of the acoustic-elastic coupled medium. Finally, the method of this paper was tested by a typical model trial.
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P-Wave Anisotropy Estimation from 3D VSP Data Acquired with Geophones and DAS at Otway Site
Authors S. Popik, R. Pevzner and A. BonaSummaryStage 2C of the Otway Project involves monitoring of a small-scale (15 kt) CO2-injection using an extensive time-lapse active seismic program. The main components of this seismic monitoring program are 4D surface seismic and 4D VSP surveys acquired before, during and after the injection. Data analysis reveals significant seismic anisotropy of the subsurface, which needs to be estimated and taken into account to improve the quality of imaging with both VSP and surface seismic data.
A wide range of offsets obtained during fifth monitoring survey of the project provides a unique opportunity for anisotropy estimation from 3D VSP data. In this study we compare geophone and Distributed Acoustic Sensor (DAS) VSP data and their applicability for anisotropy analysis. Analysis of DAS data gives anisotropy parameters for the entire depth of the well.
We estimate P-wave anisotropy by analyzing direct-wave VSP arrival times. The study demonstrates significant presence of both polar and azimuthal anisotropy. While vertical-plane anellipticity remains almost constant at 0.1 level for the whole depth range, azimuthal anisotropy changes significantly with depth: from negligibly small in the shallow part with significant increase below the 600 m depth, which most probably indicates the change of stress field at this depth.
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A Comparison of Predicted and Actual Reservoir Quality of Geothermal Projects in the Slochteren Formation
Authors L. Borst, N. Buik, W. Van Leeuwen and N. ShawSummaryNow that four geothermal projects have successfully been completed in the Slochteren Formation, the formation has proven as a valid aquifer for geothermal heating purposes. Before drilling a project, the local reservoir parameters need to be determined in order to determine the economic feasibility of a project. However, predicting this is not an easy task: permeabilities are often strongly overestimated, while temperatures and (net) reservoir thicknesses are often underestimated. This has several causes: first, the available resources for geothermal projects are limited. Therefore, geothermal feasibility studies need to be done with limited amount of time using publicly available data, mostly from hydrocarbon wells. Second, these hydrocarbon wells are drilled with a different objective than geothermal wells, which introduces difficulties when translating the datasets into one another. Thirdly, not all planned geothermal project locations have a high density of well data, which can introduce a large uncertainty in interpreted reservoir properties. As a result, comparing data from these indicative studies to the actual results after drilling of the well discloses certain discrepancies. This study helps to understand where these discrepancies come from, and may improve the accuracy of the estimated geothermal doublet performance on basis of hydrocarbon well data.
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Rock Physics Modelling of Gas Dissolved in Water Sandstone, Nakajo Field, Japan
Authors T. Fukano, T. Mizukami, T. Aoyama and Y. MaeharaSummaryNatural gas dissolved in water (GDW) is a common form of hydrocarbon occurrence in Japan, and gas production from the GDW accounts for 17% (approximately 290 mmscf/day) of total natural gas production in the country. Nakajo field is one of the fields which has long production history from the GDW reservoir. However, as GDW sandstone itself has not been well understood in aspect of the petrophysics and rock physics behaviour, it was a new finding for us that gas-effect and gas-effect-like sonic responses were observed in the GDW sandstone. In this paper, we show result of rock physics modelling, fluid substitutions, synthetic seismogram calculations, wedge modelling and AVO modelling for GDW sandstone. The rock physics modelling results revealed presence of isolated gas in GDW reservoir. Besides, water saturation estimated from rock physics modelling was regarded as useful tool to detect GDW reservoir with gas isolation. An application to seismic data is also encouraged according to synthetic seismogram calculations and AVO modelling. These outcomes allow a better evaluation approach of the surrounding area where future exploration and development potential may exist.
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Role of Prolonged Successive Fluid Flow on the Performance of Relative Permeability Modifiers in Gas Reservoirs
Authors F. Alshajalee, M. Seyyedi, M. Verrall, C. Wood and A. SaeediSummaryExcessive water production is becoming common in many petroleum reservoirs. Relative permeability modifiers (RPM) have been used to disproportionately reduce water permeability (DPR) with minimum effect on the gas/oil phases. This manuscript reports the results of an experimental study where we examined the effect of prolonged successive water-gas injection on RPM’s performance in gas/water system. The results show that the volume of water coming in contact with the polymer-treated porous medium has a direct impact on the extent of polymer swelling and thus the water permeability of the medium. It was also shown that over a large volume of gas injection, treated porous medium presents a better permability for gas at later times compared to the early times of injection. The reason could be the dehydration of the polymer layer adsorbed to the pore surfaces of the medium. It was found that successive water-gas injection could lead to stronger performance of polymer towards reducing water permeability, but it comes with the cost of a further reduction in gas relative permeability.
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Seismic Noise Attenuation Based on Higher-Order Directional Total Variation
More LessSummaryNoise attenuation is one of the key problems in seismic data processing. Total variation (TV) has played an important role in seismic data denoising and reconstruction. We develop a high-order directional total variation method for seismic data denoising that considers the structural direction of the seismic data. It involves a parameter to balance higher-order derivatives, thereby reducing the staircasing effect of the bounded variation functional. We test the method on a model where the data are contaminated by different types of noise. The corresponding denoising performance is compared with the TV and conventional directional total variation method from two aspects of signal-to-noise ratio and effective signal leakage degree. The model test and field data application illustrate the advantage of this functional as a regularization term for seismic noise attenuation.
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Squeezed Diapirs of the Timan Pechora Basin: Structure, Evolution and Petroleum Prospectivity
Authors K. Sobornov, I. Korotkov, K. Kudryavtsev and R. AnisimovSummaryReprocessing and integrated interpretation of vintage and newly available data provided new insight into structural framework of thrust belt in the northeastern part of the Timan Pechora basin. It showed that structural evolution of the fold and thrust belt was influenced by the multiphase development of salt diapirs which finally were squeezed during pulses of the orogenic shortening. This was accompanied with expulsion of salt and the development of divergent thrusting. The improved seismic imaging has allowed for more accurate definition of the structure and stratigraphy below thrust sheets including salt sole in frontal zone of the fold and thrust belt. The updated interpretation shows new exiting opportunities for petroleum exploration provided by subsalt traps.
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Stratigraphic Forward Modelling Applied to Reservoir Characterisation of Pre-Salt Carbonate Reservoirs, Santos Basin, Brazil
SummaryThis work proposes the use of stratigraphic forward modelling to test and quantify concepts about the evolution of the carbonate platform of a Pre-Salt field, as well as to use the results as trends for stochastic simulations of facies in geocellular reservoir models. The facies model was performed in three steps: (1) facies interpretation in the wells using rock data (core and sidewall samples) and image logs; (2) forward modelling simulation to control the carbonate reservoir geometry and low-frequency heterogeneities; (3) stochastic simulations of the facies, which aims to generate a high-frequency variability of facies and honour the well data. Subsequently, this final facies model, based on geological knowledge and geostatistic approach, will be the background for the propagation of the petrophysical rock properties (porosity and permeability).
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Characterization and Modeling of the Vug and Fracture Network Affecting a Carbonate Reservoir (Kmz - Mexico)
SummaryThe Cretaceous reservoir of the KMZ field consists of brecciated, carbonate rocks characterized by the presence of a complex system of natural fractures and solution vugs. As this high-permeability system plays a major role on the fluid circulation in the field, it is crucial to build-up a 3D model in order to quantify its dynamic impact. To do this, we applied the methodology for the analysis of fractured reservoir FracaFlowTM developed by the IFPEN/Beicip-Franlab group, integrating BHI data, structural information (3D seismic) and dynamic data.
Both diffuse and fault-related fractures were recognized in the field, whereas vugs largely affect mainly the brecciated layers of the reservoir. The innovation of the present study is the modeling of the vugs, with the software FracaFlowTM, as independent objects overprinting the matrix properties and distributed independently from fractures. This allows to take into account and calibrate separately the permeability of the vugs and fractures.
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Seismic Acoustic Impedance Estimation by Learning From Sparse Wells via Deep Neural Networks
Authors H. Di, X. Chen, H. Maniar and A. AbubakarSummarySeismic acoustic impedance is one of the most important properties closely related to the subsurface geology, and thus robust acoustic impedance estimation from seismic data is an essential process in subsurface mapping and reservoir interpretation. For compensating the limited bandwidth in seismic data, one feasible approach is to integrate 3D seismic volume with 1D wells that are usually sparsely distributed within a seismic survey, and such integration aims at finding the optimal non-linear mapping function between them. Most of the existing mapping methods, particularly these powered by machine learning, are performed in 1D and/or require down-sampling of well logs to the seismic scale, which run of the risk of limiting the estimation valid only around the training wells and fail to provide consistent prediction throughout the entire seismic survey.
We present a semi-supervised learning workflow for estimating the acoustic impedance over a given seismic survey by learning from a small number of sparsely-distributed wells via two deep neural networks. Applications to the synthetic SEAM dataset of a complex salt intrusion demonstrates its capability in reliable seismic and well integration, particularly in the zones of poor seismic signals due to the presence of geologic complexities, such as saltbodies.
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Diffraction Separation and Holistic Migration: High-Resolution Imaging Beyond Nyquist
Authors L. Gelius and V. Stenbekk ThorkildsenSummaryIn case of a broken hologram, an image of the complete object can still be obtained from one of the fragments. The reason is that each diffraction point of the object sends out waves that reach every point on the hologram. As an analogy, we propose to separate diffractions from standard seismic reflection data. The use of a decimated version of such data (violating the Nyquist sample condition) should still contain all necessary information to obtain an image of the finer details of the subsurface employing the concept of holographic migration. The feasibility of the proposed approach is supported by a field data example from the Barents Sea.
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Langevin Dynamics Markov Chain Monte Carlo Solution for Seismic Inversion
Authors M. Izzatullah, T. van Leeuwen and D. PeterSummaryIn this abstract, we review the gradient-based Markov Chain Monte Carlo (MCMC) and demonstrate its applicability in inferring the uncertainty in seismic inversion. There are many flavours of gradient-based MCMC; here, we will only focus on the Unadjusted Langevin algorithm (ULA) and Metropolis-Adjusted Langevin algorithm (MALA). We propose an adaptive step-length based on the Lipschitz condition within ULA to automate the tuning of step-length and suppress the Metropolis-Hastings acceptance step in MALA. We consider the linear seismic travel-time tomography problem as a numerical example to demonstrate the applicability of both methods.
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A New Integrated Workflow to Generate Avo Feasibility Maps for Prospect De-Risking
Authors P. Avseth, I. Lehocki, K. Angard, T. Hansen, E. Shelavina and S. SchjelderupSummaryA new integrated workflow for generation of AVO feasibility maps to be used in prospect de-risking is presented. We demonstrate the workflow on data from the Barents Sea. The methodology enables rapid extrapolation of expected rock physics properties away from well control, along selected horizon, constrained by seismic velocity information, geological inputs (basin modelling, seismic stratigraphy and facies maps) and rock physics depth trend analysis. The workflow should allow for more rapid, seamless and geologically consistent DHI de-risking of prospects in areas with complex geology and tectonic influence. The AVO feasibility maps can furthermore be utilized to generate non-stationary training data for AVO classification.
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Rock Physics Analysis of Volcanic Lava Flows and Hyaloclastites
Authors P. Avseth, J. Millett, D. Jerram, S. Planke and D. HealySummaryA study is conducted to investigate the rock physics properties of volcanic facies from available core measurements (72 samples available from Iceland and Hawaii). The main goal is to investigate the rock physics properties of a set of volcanic rock samples, and to establish predictive rock physics templates for these rocks, as a function of facies and rock texture, fluids and minerology. We focus on lava flows and hyaloclastites from Iceland and Hawaii. We find that both these facies can be modelled using modified Hashin-Shtrikman upper elastic bounds, and we create rock-physics templates for varying porosity and fluid saturations. Dry or gas-filled hyaloclastite facies plots with low acoustic impedances and low Vp/Vs ratios and are nicely separated from brine-filled hyaloclastites. Dry and wet high-porosity/high-permeability vesicular lavas will have similar AI and Vp/Vs values, and therefore these rocks will be more difficult to discriminate seismically.
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