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Petroleum Geostatistics 2015
- Conference date: 07 Sep 2015 - 11 Sep 2015
- Location: Biarritz, France
- ISBN: 978-94-6282-158-3
- Published: 07 September 2015
21 - 40 of 77 results
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Channel Simulation Using L-system, Potential Fields and NURBS
Authors G. Rongier*, P. Collon, P. Renard and J. RuiuChannelized environments have huge implications in many fields, from hydrogeology to mineral ressources or geotechnic. Their modeling is so of prime importance. However, some of their characteristics make this a difficult task. This is especially the case of their high continuity that is arduous to preserve while ensuring data conditioning. We propose to rely on a formal grammar system, the Lindenmayer system or L-system, to stochastically generate the channel morphologies resulting of the deposition processes. The L-system considers a channel as a succession of channel elements and puts together those elements based on user-defined rules and parameters, such as the element size or the angle between two consecutive elements. The succession of elements is then interpreted to generate non-rational uniform B-splines (NURBS) representing straight to highly meandering channels. Conditioning to hard and soft data is done through the use of potential fields that define attractive or repulsive forces toward the data. L-systems appear to be highly flexible in the generation of various channel morphologies. Preliminary results show that the method manages to simultaneously honor conditioning data and preserve at best the channel variations defined by the parameters.
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Taking into Account Uncertainty on Fairway Borders for Lateral Offset Stacked Channels (LOSCs) Simulations
Authors D. D'Or*, E. Braccini and P. BiverAmong the process-based methods, the Lateral Offset Channels (LOSCs) simulation method has been especially designed to simulate logical chronological sequences of channels. The last (most recent) channel observed on spectral maps is fitted with a B-spline. To simulate the older channels in the sequence, the control points of the B-spline are moved along a parabolic path towards the fairway centerline, thus modifying the original B-spline in a logical way. In this paper, we particularly emphasize on the uncertainty on the fairway borders and show how actual borders corresponding to various scenarios can be drawn and how the channels simulation is adapted accordingly. In particular, we show on a field case that a larger fairway results in more meandering channels than a narrower one. All channels in a sequence are consistent with each other and can be conditioned to well data.
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Hierarchical Parameterisation and Modelling of Deep-water Lobes
Authors L. Zhang, T. Manzocchi* and A. PonténRecent studies characterizing outcrop analogues of deep-water lobe reservoirs have demonstrated that these deposits are stacked in a hierarchical manner with characteristic element scales that vary between turbidite systems. Static connectivity and dynamic numerical modelling studies of idealized, non-hierarchical lobe systems have identified the presence of discrete net-gross or amalgamation ratio thresholds that control connectivity and flow. The objectives of the current work are to compile a geostatistical description of the hierarchy; to develop a hierarchical modelling scheme able to apply these conceptual and quantitative constraints; and, from these, to assess the importance of honoring the hierarchy in reservoir modelling.
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Preserving Geological Realism of Facies Estimation on the Brugge Field
Authors Y. Chang*, A.S. Stordal and R. ValestrandFacies estimation using ensemble-based methods has been a popular and challenging problem in reservoir history matching. The challenges come from the difficulty of handling the discrete facies variables and preserving the geological realism in the updated facies models from ensemble-based methods. This work proposes the use of a normal score transformation as the facies parameterization approach coupled with Iterative Adaptive Gaussian Mixture (IAGM) filter to estimate the facies and non facies variables simultaneously on the complex reservoirs. We present the novel idea of using dummy wells to condition the facies modeling process for continuous channel regeneration. The overall workflow is an interaction between the data assimilation and the facies property modeling process. The proposed workflow is demonstrated on the Brugge field case and the data assimilation results provide geologically realistic facies models with better match of historical production data.
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Seismic Wavelet Estimation and Uncertainty Quantification Using a Parametric Model
Authors J. Skauvold*, J. Eidsvik and U. TheuneEstimation of seismic wavelets from seismic amplitude data and reflection coefficient series is a difficult problem with numerous solutions. Here, the wavelet is represented by a parametric form, and parameters are estimated by Bayesian inversion. Parametrising gives increased parsimony and interpretability, but reduces flexibility compared with more generic estimation approaches.
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Multiscale Geostatistical History Matching Using Block Direct Sequential Simulation
Authors C. Marques*, L. Azevedo, V. Demyanov, A. Soares and M. ChristieThis paper proposed a multiscale geostatistical history matching methodology using a new algorithm. The challenge of this work is the development and the application of an algorithm that couples different geological scales by recurring to Block Direct Sequential Simulation. In order to speed-up the history matching procedure we first optimize the reservoir model at a very coarse grid which is then used as an auxiliary model to perform the history matching at a very fine scale. With the development of this workflow is expected a better coarse and fine solution, an improved and more reliable reservoir model with a significant reduction of computing time and with a good integration of dynamic data in the static model. We show this novel approach in a challenging synthetic case study based on a fluvial environment.
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Flexible Objects - A Way to Generate more Realistic Object-based Simulations
Authors A. Walgenwitz*, D. Allard and P. BiverThe object-based simulation is revisited by handling objects with complex geometry to overcome the lack of realism of standard object-based simulation. GPGPU capabilities (General-Purpose Computing on Graphics Processing Units) are used to achieve the intensive numerical computations and intensive geometric queries. The case study presented to illustrate the technique is the modeling of the internal architecture of a lobe complex in a reservoir of Western Africa.
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Acceleration of Stochastic Seismic Inversion in Open CL-based Heterogeneous Platforms
Authors T. Ferreirinha, R. Nunes, L. Azevedo*, A. Soares, F. Pratas, P. Tomas and N. RomaThe recently proposed Geostatistical seismic AVO inversion algorithm uses direct sequential simulation and co-simulation as the model parameter space perturbation technique. To reduce the execution time of this iterative geostatistical inversion procedure, a simplified version of the sequential simulation algorithm was parallelized to exploit multi-core Central Processing Units (CPUs). By applying a straightforward functional decomposition of the algorithm, an acceleration of up to 3.5x was observed for a quad-core CPU. This solution is limited not only in scalability but also in the capacity to exploit modern heterogeneous computing systems composed of multiple processors. An efficient parallelization approach of the geostatistical seismic AVO inversion algorithm is here proposed, by considering highly heterogeneous platforms composed by several devices with different computational capabilities. Such a flexible solution is achieved by using the OpenCL API, allowing each part of the algorithm to be easily migrated among the several coexisting CPUs and GPUs.
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Simulation of Facies Uncertainty in Field Development
Authors C. Dubreuil-Boisclair*, T. Ek, R. Hanea, C. Otterlei, E. Zachariassen and B. MassartThe aim of this paper is to assess the use of a recent facies modelling method (Adaptive Plurigaussian Simulation or APS) for facies-uncertainty analysis and sensitivity study in a complex field-development project. This method provides multiple facies realizations that honours all prior data (well, seismic, and geological concept) can be updated when conditioning to dynamical data, using ensemble methods, when production starts. The method is set up as part of an integrated and automated workflow (Fast Model Update or FMU) for reservoir modelling and characterization that is implemented in Statoil. We demonstrate that the use of APS within an FMU workflow allows for fast simulation of facies sensitivities that are reflected in the production profiles.
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Testing Alternative Geological Heterogeneity Representations for Enhanced Oil Recovery Techniques
Authors E. Tamayo-Mas*, H. Mustapha and R. DimitrakopoulosThis paper analyzes the effects of geological heterogeneity representation in a producing reservoir, when different stochastic simulation methods are used to assess the consequent effects on flow responses for different EOR techniques employed. First, the spatial heterogeneity of a fluvial reservoir is simulated using three different stochastic methods: (1) the well-known two-point sequential Gaussian simulation (SGS), (2) a multiple-point filter-based algorithm (FILTERSIM), and (3) a new alternative high-order simulation method that uses high-order spatial statistics (HOSIM). Numerical results show that SGS suffers from the inability of describing the highly permeable channel network whereas FILTERSIM better reproduces this connectivity. By means of the recent HOSIM, a more appropriate description of the curvilinear high-permeability channels is obtained. Second, the realizations generated above represent permeability fields in EOR numerical simulations. In particular, four different methods are considered, namely: (1) surfactant, (2) polymer, (3) alkaline-surfactant-polymer and (4) foam flooding processes. The numerical results show that properly reproducing the main geological features of the reference images has a higher impact if surfactant or alkaline chemicals are injected rather than if polymer, which acts by reducing the reservoir permeability, or foam, which mitigates the heterogeneities caused by higher permeability layers, are introduced.
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Indicator Variogram Models - Do we Have much Choice?
Authors O. Dubrule* and P. SungWith indicator simulation techniques that do not specify the underlying random set model, there is a risk of using an indicator variogram model that does not correspond to any known random set model. As a result this model may be an invalid indicator model, even though it may be a valid model for a multigaussian variable. Surprisingly, if there are known necessary conditions for an indicator variogram model to be valid, on the other hand there is no proven sufficient condition. If we make an inventory of known variogram models that remain valid as 3D indicator variogram models, the only one to emerge unchallenged seems to be the exponential model. We take this opportunity to review the properties of the exponential model in the context of indicator co-simulation, taking advantage of the work of Carle (1996). We see that the use of the transiogram model for interpreting variograms allows a much easier geological interpretation of these models. We also see that there is some flexibility in using exponential models, thanks to the addition of dampened hole-effect models in 1D.
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Recent Advances for Facies Modelling in Pluri-gaussian Formalism
Authors P.Y.A. Biver*, D. Allard, F. Pivot and P. RuellandThe Pluri-Gaussian simulation (PGSim) formalism has been initiated in the nineties (see Le Loch and Galli 1997). This methodology has been used in numerous mining and petroleum industry applications. In this paper, we come back on this technique to present some recent interesting extensions. The first extension concerns the truncation (or assignation) diagram; using the technique developed in Allard and al. (2012), it is possible to build complex diagrams (not just composed of rectangles) and to adjust them to target proportions. This methodology provides new modelling possibilities with fit for purpose diagrams. Some applications to reproduce complex shapes similar to those observed in nature are presented. The second extension enables the use of the Pluri-Gaussian formalism in an estimation context. The idea of using an existing continuous variable (generally a geophysical attribute) to perform a truncation and to obtain a facies model was proposed in Biver and al. (2012). We present here the generalization of this formalism to Pluri Gaussian context. This generalisation allows us to perform a facies estimation consistent with two geophysical attributes
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Modeling Three Ways from Electro-facies - Categorical, E-facies Probabilities, and Petrophysics with Assignment
Authors D.L. Garner*, J. Yarus and M. SrivastavaGeomodeling for petroleum reservoirs is conventionally done hierarchically by facies to establish regions within which rock and fluid properties can be considered “stationary.” Many reservoir models do not use depositional facies description, but use “electro-facies” created from clustering petrophysical log curves. This paper compares three approaches to the development of e-facies geomodels, 3D models of categorical codes to be used as stationary domains within which rock and fluid properties can be simulated. The first approach uses e-facies codes developed through cluster analysis as conditioning data and uses a method for simulating categorical variables, plurigaussian simulation, to directly build a 3D model of the e-facies. The second approach uses petrophysical logs at the wells as conditioning data and uses a standard method for co-simulating continuous variables to build 3D models of the log responses; these are then converted to e-facies using the rules developed through cluster analysis. The third method works directly with the e-facies probabilities that most cluster analysis techniques can provide. These probabilities are co-simulated as continuous variables in 3D, ensuring they are bounded and sum to 1, and a unique e-facies code is assigned, by taking the e-facies with the maximum probability at each location.
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Integrating Spatio-temporal Rules for Surface-based Reservoir Modeling
Authors Y. Wang and T. Mukerji*A rule induction methodology is demonstrated to generate surface-based models of channel-network systems by transforming numerical geological process outputs into statistical rules controlling the channel network simulation. The methodology is applicable not only to outputs from numerical simulators but also to satellite images of channel network systems. We use a multi-scale line tracking algorithm (MSLTA), to extract the channel network. Based on the distribution of bifurcation points, realizations of network skeletons are generated using a space colonization algorithm. Finally geobodies and surfaces are added around the skeleton. Surface-based modeling and rule-based algorithms provide promise in capturing realistic geometric evolution of facies geobodies without the need for computationally expensive numerical solutions of process-based models, provided good rules are available to guide the algorithm. Process-based model results and physical tank experiments serve as good 'warehouses' of statistics and rules for rule-based modeling.
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Geostatistical Simulations on Irregular Reservoir Models Using Methods of Nonlinear Geostatistics
Authors V.N. Zaytsev*, P. Biver, H. Wackernagel and D. AllardClassical approaches to geostatistical simulations are not applicable directly on irregular reservoir models (such as Voronoi polygon and tetrahedron meshed models). One of the main difficulties is that the block marginal distributions are unique for every block due to volume support effect. We propose a methodology for geostatistical simulations which overcomes this difficulty in an analytical manner and provides a robust utilization of the small support petrophysical property distribution and the covariance model for irregular reservoir models. The proposed solution is based on the discrete Gaussian (DGM) model and operates directly on blocks of the target grid. This solution is also capable to improve the quality of the classical reservoir models, such as tartan meshes, by including the volume support effect into consideration and thus-providing geologically more realistic results. Applications to Voronoi polygon grid with local grid refinements and to a tartan-meshed offshore gas reservoir model are demonstrated.
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Geostatistics on Unstructured Grid - Coordinate Systems, Connections and Volumes
Authors H. Gross* and A.F. BoucherThe current trend in reservoir simulators is to solve transport of energy and flow equations on unstructured grids. This work addresses three challenges for geomodelers wanting to perform geostatistics directly on unstructured grids: (1) the large range of cell volumes and their arbitrary shapes, (2) the complex cell topology and its need for explicit connection specifications and (3) the use of alternate coordinate systems to better conform to geological features. This work uses triangular, hexagonal, and tetrahedral 3D grids to demonstrate the adaptation of geostatistical algorithms on unstructured grids. Hard data conditioning and locally-varying trends are also addressed. Finally we present three approaches to simulate on unstructured grid (1) the simulation on cell centroids, (2) the simulation on a finely discretized grid followed by upscaling and (3) a direct cell geostatistical algorithms.
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An Unstructured Depositional Grid for Property Modeling
Authors A. Benabbou*, C. Daly, L. Macé, A. Levannier and C. BuchholzThe presentation first develops a transform from geological space to depositional space based on large deformation elasticity. A depositional grid is constructed using this mapping. It is shown that this grid, even though it is unstructured and capable of modeling complex geology, can be used directly in geostatistical modeling without a need for an upscaling step as is more usually the case for performant unstructured grids.
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Value of Information Analysis of Geophysical Data for Drilling Decisions
Authors J. Eidsvik*, T. Mukerji, D. Bhattacharjya and G. DuttaValue of Information (VOI) analysis is conducted for different geophysical data (seismic and electromagnetic data). VOI is a concept in decision theory for analysing the value of obtaining additional information, before purchasing and revealing the data. Gathering the right kind and amount of geophysical information is crucial for resolving difficult reservoir decision situations. We focus on drilling decisions, and structure situations according to the spatial decision alternatives and value function complexity. The geostatistical modeling plays an integral part of the prior decision making, and for the pre-posterior evaluation of the various data gathering schemes.
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Uncertainty Assessment Driven Exploration Program Modification - A Case Study
Authors O.A. Gorbovskaia* and B.V. BelozerovFor the last decade multiple realizations geological modelling has become a widely used practice in petroleum industry. Integrated analysis of geological and geophysical data available at the moment via multivariate modelling may be applied not only for probabilistic methods of oil-in-place (OIP) estimation but also may help to better understand reservoir and associated risks and therefore affect the exploration and development decisions. The work deals with a case study of exploration planning focused upon OIP assessment correction. It shows an example of multivariate 3D geological modelling application for prognosis of the results obtained after one or another exploration option. The approach discussed allows quantitative assessing an effect of drilling a well at alternative locations on uncertainty level decrease. Proactive analysis of outcomes expected is thought to be a powerful tool for improvement of exploration program from the standpoint of both expenses optimization and risk decrease.
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Efficient Optimization of Exploration Drilling Campaigns with Convergent Information Bounds
Authors M. Lilleborge*, J. Eidsvik and R. HaugeWe discuss a Bayesian Network (BN) with 42 nodes, of which 25 are leaf nodes that represent actual petroleum prospects in the North Sea where we could choose to collect data. We look at the case where the data gathering is carried out as a seasonal campaign with m exploration wells, and the question is: Where should they be drilled? The complexity of the problem is such that for large m or for larger networks, the optimal observation set problem is not computationally feasible through exact calculations. We introduce a method for computing upper and lower bounds inspired by the Junction Tree Algorithm to do a more efficient search for the optimal drilling campaign. Our algorithm improves the bounds until they are sufficiently tight, and our construction of the upper and lower bounds results in an extremely efficient search for the optimal observation set for exploration wells in the North Sea petroleum prospect case.
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