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74th EAGE Conference and Exhibition incorporating EUROPEC 2012
- Conference date: 04 Jun 2012 - 07 Jun 2012
- Location: Copenhagen, Denmark
- ISBN: 978-90-73834-27-9
- Published: 04 June 2012
81 - 100 of 948 results
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Coupled Static / Dynamic Modeling for Improved Uncertainty Handling (SPE 154400)
Authors M.P. Kaleta, R. Bennett, J. Brint, P. Van Den Hoek, J. Van Doren, G. Van Essen, T.J. Woodhead and B.W.H. Van BeestIn the petroleum industry history-matched reservoir models are used to aid the field development decision-making process. Traditionally, models have been history-matched by reservoir engineers in the dynamic domain only. Ideally, if any changes are required to static parameters as result of history matching the dynamic model, then these should be reflected directly in the static reservoir model. This permits consistency between the static and dynamic domain. In addition, static model uncertainties are often not evaluated in the dynamic domain, which could result in the detailed modeling of geological features that have no impact on the dynamic behavior and the resulting development decision. This paper demonstrates a workflow where the reservoir simulator and static modeling package are closely linked to promote a more integrated approach and to enhance the interaction between the subsurface disciplines. Using either the simulator or the static modeling package as the platform, the output of the workflow is a sensitivity analysis of the uncertainties related to structure, rock properties, fluids and rock-fluid interactions. Next, computer-assisted history matching methods (i.e. adjoint-based and Design of Experiments) are used to find the parameter values that result in a successful history match. The workflow will be demonstrated both on a synthetic model and on a reservoir model from a real field case. This methodology results in history-matched models and a better understanding of the static and dynamic subsurface uncertainties, leading to more informed decision-making. The method presented here can significantly enhance the awareness of the impact of both static and dynamic subsurface uncertainties on development decisions. In addition, it offers a platform where all subsurface professionals can more optimally combine their efforts to improve the integrated understanding of reservoirs.
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Multi-phase Well Testing to Calibrate Relative Permeability Measurements for Reservoir Simulation (SPE 154851)
Authors A. Green, A.C. Gringarten and T.M. WhittleSpecial core analysis (SCAL) is the standard method for estimating relative permeabilities. These, however, must be upscaled for reservoir simulation and the upscaling process creates uncertainties that are propagated to field performance forecasts. This paper describes a six-stage well testing procedure to calibrate relative permeabilities for reservoir simulation and to reduce uncertainties in relative permeability end points and curvature. The well test includes: (1) single phase oil production; (2) build up; (3) single phase water injection; (4) falloff; (5) two-phase oil and water production; and (6) a final build up. The final build up is initiated at minimum well productivity. Transient pressure analyses of the first build up (2) and the fall off (4) provide the single phase mobility for each fluid at respective saturation end points. These yield an estimate for endpoint water relative permeability using a Corey type relative permeability correlation. Analysis of the second build up (6), on the other hand, yields an estimate of the minimum mobility. Uncertainty in oil and water relative permeability curvature (which depends on Corey exponents) is reduced using all three mobility estimates, while uncertainty in end point saturations can be reduced by running wireline logs at the onset of the test and of the following injection. The procedure is demonstrated by simulating a newly drilled well in an oil-water homogeneous reservoir above the bubble point pressure. The impact of relative permeabilities on water breakthrough and and oil production is shown to be significant in such an oil field developed by water flood. Sensitivities to reservoir heterogeneity, water cut during the flow back period, numerical dispersion, and capillary pressure have also been explored. Information provided by the proposed test and interpretation procedure allows improved field development decisions early in field life.
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Use of Water Chemistry Data in History Matching of a Reservoir Model (SPE 154471)
Authors D. Arnold, M.A. Christie, V. Demyanov and O. VazquezProduced Water Chemistry has been included in the history matching of reservoir simulations. Generally, in conventional history matching, the water chemistry is not considered as an extra constraint. The chemistry of the different types of water in a reservoir, such as aquifer, connate and seawater is very different, and can be traceable. Produced Water Chemistry is the main source of information to monitor scale precipitation in oil field operations. The objective of this paper is to evaluate the effect of adding produced water chemistry information as an extra constraint history matching a modified version of the PUNQ-S3 reservoir model. The PUNQ-S3 model is a synthetic benchmark case that has been used previously for history matching uncertainty quantification. Conventional historical production data (gas, oil rate and pressure) from six production wells are supported by the water chemistry tracer data from the wells that produce water in the history period. The different types of water are traced through their distinctive chemistries, namely aquifer, connate (formation) and sea (injection) water. Geological model is matched by varying porosity and permeability, both horizontal (kh) and vertical (kv) according to the prior beliefs about the reservoir geology (layering, spatial correlation and anisotropy). Two history matching scenarios are considered: including and not-including the Produced Water Chemistry (PWC) as extra matching constraints. Stochastic Particle Swarm Optimization (PSO) algorithm is used to generate ensembles of history matched models, which characterise the uncertainty of the reservoir prediction. The confidence intervals for the forecast are computed using NA-Bayes (Neighborhood Algorithm) technique, which evaluates the posterior probability of the generated models. Finally, to evaluate the effect of adding PWC in the history matching, the Bayesian confidence intervals (P10-P50-P90) generated by each method were compared.
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Integrated Interpretation for Pressure Transient Tests in Discretely Fractured Reservoirs (SPE 154531)
Authors K. Morton, R. Booth, F.J. Kuchuk and P. De Brito NogueiraIn 2005, Petrobras discovered a fractured Albian carbonate reservoir in Campos Basin. During the evaluation of an appraisal well, a full sequence of well tests (DSTs) and a 4-month extended well test (EWT) were performed to monitor reservoir behavior and to define the most probable geological reservoir model before the final development decision was made. While the results of the well test sequence were sufficiently favorable for development, the well test analysis raised concerns about the quantitative use of these tests for reservoir characterization. The seismic sections of the field indicated faulting, and open fractures were interpreted from image logs in the appraisal wells. However, the response of the DSTs and EWT did not indicate classical dual porosity type behavior that is consistent with an extensive connected fracture network system. The fractures in this reservoir are considered to be predominantly open in one direction only. Few methods exist for the interpretation of the pressure transient response of discretely fractured reservoirs where fractures provide conduits for fluid flow and displacement, but where the fracture network is poorly connected compared to dual porosity models. In this paper, we first outline the gaps in the existing pressure transient well test interpretation methodology for these reservoirs, then we introduce two new techniques developed to address these gaps: 1) A reservoir model-based inversion technique for parameter estimation from pressure transient data, and 2) A boundary element method for determining the pressure transient behavior of the reservoir with arbitrarily distributed finite and/or infinite conductivity vertical fractures. We define a new integrated interpretation methodology for reservoirs with discrete natural fractures making use of these techniques and incorporating openhole log data, seismic and the preliminary geological reservoir model. Finally, we illustrate the use of the methodology using the tested well.
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Reducing Reservoir Uncertainties Using Advanced Wireline Formation Testing (SPE 154426)
Authors S. Cantini, C. Baio, D. Baldini, M. Borghi, M. Gigliotti, F. Italiano, D. Loi and S. MazzoniSeveral offshore gas fields are present in Adriatic Sea (Italy), producing since the 60s. In these assets the gas is mainly produced from multilayer metric sand reservoirs. The declining production in these mature fields is normally offset by drilling new deviated wells. Recent technology evolution shifted the focus from metric reservoirs to thinly laminated intervals (thin beds), until now not produced due to difficulties in indentifying gas bearing zones. While gas identification in metric reservoirs can be achieved with standard petrophysical measurements, thin beds are challenging since lamination thickness is half inch or less and even advanced petrophysical logs struggle in discriminating gas from water in this environment. Conventional pressure gradient approach also does not work, since thin beds are often overpressurized and pressures are supercharged due to low mobility. A new wireline formation testing approach for thin beds to discriminate gas from water zones was introduced, using a dual packer string with downhole fluid analysis capabilities, including fluid density measurement. This provided the possibility of testing very low permeability zones with high uncertainties in saturations. The possibility to verify gas presence in zones with high uncertainties saved the cost of multiple well testings, optimized the completion strategy of the different reservoirs and allowed to increase the field production and reserves. Dual packer tests were also successfully carried out in the basinal and slope facies of foreland basin, a shale formation underlying the multilayer reservoir sequence never considered before a real reservoir, revealing potential for gas production. Several gas fields today producing from metric reservoirs will be revisited in the very near future in order to start production from thin beds, until now untouched. The advanced wireline formation testing approach described in this paper will certainly play a key role in optimal exploitation of thin beds gas reserves.
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Decision Making under Uncertainty in EOR - Applying the Least Squares MonteCarlo Method in Chemical EOR Implementation (SPE 154467)
Authors A. Alkhatib, M. Babaei and P.R. KingThis study builds on the previous work of the author in adapting the LSM (Least Squares MonteCarlo) method to an EOR context in order to value flexibility in the implementation of a surfactant flood and to produce the optimal policy. The LSM algorithm was developed in MATLAB and SchlumbergerC"s Eclipse was used as the reservoir simulator. The main focus of the algorithm was to consider the uncertainty in parameters that vary in time. The technical uncertainties considered were the residual oil saturation to the surfactant flood and surfactant adsorption while the main economic uncertain parameters considered were oil price, surfactant cost and water injection and production costs. The study is divided into two main sections: the first section considered the uncertainty in technical and economic parameters using a homogenous synthetic model, the second section considered the effects of the uncertainty of these parameters on a heterogeneous model based on permeability data from SPE Comparative Solution Project, Model 2. In this case, heterogeneity is considered as another uncertain parameter by having the heterogeneous permeability field realizations vary with time. This is achieved by using upscaled models and progressively replacing them with finer models. This procedure represents the increasing state of knowledge in terms of our understanding of the reservoir with time. The results show that the LSM method provides a decision making tool that was able to capture the value of flexibility in surfactant flooding implementation. It also demonstrated that it is economical to implement surfactant flooding under uncertainty compared with the evaluations of traditional methods which produce uneconomical outlooks under the same conditions. Another advantage of this method is that it considers the value of information during the life of an EOR project which might undergo an alteration of the implementation strategies at different decision times.
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Regularization in History Matching Using Multi-objective Genetic Algorithm and Bayesian Framework (SPE 154544)
Authors M. Sayyafzadeh and M. HaghighiHistory matching is an inseparable part of reservoir characterisation which is a highly nonlinear inverse problem and suffers from ill-posedness. Different regularisation methods such as Tikhonov regularisation and Bayesian framework have been used to overcome the ill-posedness using prior knowledge. In this study, the application of a multi-objective genetic algorithm (GA) in the history matching as a regularisation and an optimisation is introduced. In this approach, two separate objective functions likelihood and prior are defined. In Tikhonov and Bayesian approach, the mentioned objectives are defined with one weighted function. In the Bayesian framework, covariance matrixes are utilised as weighting factors for each parameter, but there is no constant to join likelihood and prior objectives. However Tikhonov relates the objectives with a weighting factor, it is a challenging task to find the optimum value for the constant in the history matching. Consequently, in these two regularisation methods, it is potential that one objective dominates the other one. To validate the approach, ECLIPSE is coupled with MATLAB. A synthetic 3 dimensional 3 phase reservoir is constructed. Gaussian noise is added to the history. After that, different approaches are used to match the history and reconstruct the reference case. Bayesian and Tikhonov regularisation with different optimisation methods, real-valued genetic algorithm and nonlinear least square Levenberg-Marquardt algorithm optimisation are used. Then, their results are compared with a multi-objective GA. The outcomes demonstrate that the proposed method converges quicker than other methods and more importantly the results are realistic. In multi-objective systems, each objective has effect on the other one. Hence, optimising a system without considering all the objectives together leads to unrealistic outcomes. Using a multi-objective GA, it would be feasible to consider all objectives togather and provide the Pareto front.
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Challenges in High Performance Computing for Reservoir Simulation (SPE 152414)
Authors E. Hayder and M.A. BaddourahHigh resolution reservoir modeling is necessary to analyze complex flow phenomena in the reservoir. As more powerful computing platforms are becoming available, simulation engineers are building larger high resolution reservoir models to study giant fields. Complexities in simulation algorithms and memory contentions are challenges to efficient use of emerging computing platforms. As new tools are available and performance of hardware and software improves, it is important to reevaluate and revise implementation details of the simulator to maintain a high level of scalability on the large number of processors. There is enormous potential in emerging technologies, such as graphic processing units (GPUs), but currently, the lack of development tools restricts their adaptation in high performance computing. Researchers in many areas of computational fluid dynamics have been able to achieve a very high level of computational performance. Such a high level is yet to be achieved in reservoir simulation. In this study, we review computational difficulties in high performance computing related to reservoir simulation and examine how improvements can be made by use of emerging technologies in this class of problems. We discuss our efforts towards improving communication and input/output (I/O) algorithms in our reservoir simulator. We also evaluate high speed interconnections, various communication libraries, etc., for parallel computations and examine how simulation performance can be improved on the latest multi-core processors. Benchmark results of various computational and I/O kernels and a summary of actual simulation results will be reviewed to illustrate current challenges and the near term outlook of high performance reservoir simulation studies.
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Improved Mobility Calculation for Finite Element Simulation (SPE 154480)
Authors A. Abushaikha, M.J. Blunt, O.R. Gosselin and T.C. LaForceWe implement a novel up-winding scheme for the mobility calculation using the computed velocities in a finite element (FE) unstructured-mesh simulator for fractured reservoirs. In the finite-element finite-volume (FEFV) numerical discretisation method, the pressure and transport equations are decoupled. The pressure is calculated using finite elements, and the saturation is calculated using finite volumes. Each element is shared between several control volumes -- three for triangles (2D-fractures) and four for tetrahedral (3D-matrix). Consequently, the saturations used in calculating the mobilities -- hence updating pressure -- are unclear. Some researchers use the average value between the elemental control volumes, or the integration points of the finite elements. For two-dimensional radial flow, this does not produce accurate saturations profiles when compared to the Buckley-Leverett reference solution. In this paper, we present a new formulation to calculate the FE mobility. We use the velocity vector, which is piece-wise constant in first order elements, to find the upstream saturation -- where the tail of velocity vector intersects an element. We compare the results of this new mobility calculation against other FEFV fractured reservoir simulators. We test the new method on a fracture network outcrop meshed using discrete fractures and matrix elements. This novel approach produces more accurate saturation profiles than previous methods even with higher order methods and better models multi-phase displacements in complex reservoir. It can be easily implemented in current FEFV based simulators.
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A Parallel Streamline Simulator for Integrated Reservoir Modelling on a Desktop (SPE 154484)
Authors M. Gaupaas, F. Bratvedt, S.K. Khataniar, A. Primera and F.P. RuanDesktop computing is undergoing a revolution with parallel processing on multi-core workstations. Parallel streamline simulators have been developed for shared memory architecture systems, using off-the-shelf compilers with an application programming interface for parallel programming. Here, we discuss the implementation and the performance analysis of a parallel streamline simulator based on native threading technology for both WindowsCB. and LinuxCB. operating systems. Although parts of the general streamline simulation algorithm are relatively straightforward to parallelize, there are several challenges that require special attention to avoid computing bottlenecks and inconsistent results across different computing environments. An efficient load balancing algorithm to avoid idle processors has been implemented, combined with a data-accumulation scheduling algorithm to ensure consistent results independent of the platform and the number of processing units. The combined performance of a multicore computer and a parallel streamline simulator offers significant opportunities for reservoir management applications. It can also increase the use of 64-bit desktop workstations that are commonly used for 3D geological modelling and the creation of applications that integrate the geosciences. Parallel scalability analysis for various model characteristics and simulator options is also analyzed. For a variety of models, we have observed an almost linear scalability for as many cores as available on a typical shared memory high-performance computer.
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A Comparative Study of Reduced Variables Based Flash and Conventional Flash (SPE 154477)
More LessSpeeding up flash calculation is a central issue in compositional reservoir simulations since phase equilibrium calculation is the most time-consuming part in those simulations. The reduced variables methods, or the reduction methods, reformulate the original phase equilibrium problem with a smaller set of independent variables. Various versions of the reduced variables methods have been proposed since the mid 80's. The methods were first proposed for cubic equations of state (EoS) with zero binary interaction parameters (BIPs) and later generalized to situations with non-zero BIP matrices. Most of the studies in the last decade suggest that the reduced variables methods are much more efficient than the conventional flash method. However, Haugen and Beckner questioned the advantages of the reduced variables methods in their recent paper (SPE 141399). A fair comparison between the reduced variables based flash and the conventional flash is not straightforward since the former is difficult to be formulated as unconstrained minimization and involves more complicated composition derivatives. With the recent formulations by Nichita and Garcia (2010), it is possible to code the reduced variables methods without extensive modifications of MichelsenC"s conventional flash algorithm. A minimization based reduced variables algorithm was coded and compared with the conventional minimization based flash. A test using the SPE 3 example showed that the best reduction in time was less than 20% for the extreme situation of 25 components and just one row/column with non-zero BIPs. A better performance can actually be achieved by a simpler implementation directly using the sparsity of the BIP matrix.
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Non-darcy Flow Numerical Simulation for Low-permeability Reservoirs (SPE 154890)
More LessWith further progress of oilfields' development all over the world, more and more low permeability reservoirs are being put in production. However, fluid flow in low permeability porous media deviates from the classic Darcy's law and instead conforms to the one of non-Darcy seepage. Most mature commercial numerical simulation softwares may cause error in simulating development performance of low permeability reservoirs. So a non-Darcy seepage numerical simulation software has been developed. In this paper, non-Darcy seepage mathematical model was proposed. In addition, on the basis of practical field and laboratory experiment data, an ideal model of five-spot well pattern was also established. Under the same reservoir condition, the non-Darcy simulation, conventional Darcy simulation and the simulation of threshold pressure gradient were conducted. The comprehensive comparison and analysis of the simulation results of Darcy flow, threshold pressure gradient flow and non-Darcy flow were provided. Research shows that compared to the results of Darcy flow, when considering non-Darcy flow, the oil production is low, and production decline is rapid; the fluid flow in reservoir consumes more driving energy which reduces the water flooding efficiency. Darcy flow model overstates the reservoir flow capability, and threshold pressure gradient flow model overstates the reservoir flow resistance. In the low permeability reservoirs, non-Darcy seepage dominates in a large scale of formation and the non-Darcy simulation result shows excellent agreement with the production data. Therefore taking the non-Darcy seepage into account is more suitable to reflect the percolation mechanism and development performance of low permeability reservoirs. This numerical simulation method has been applied successfully in Shengli oilfields.
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Machine Learning Methods to Speed up Compositional Reservoir Simulation (SPE 154505)
Authors V. Gaganis and N. VarotsisCompositional reservoir simulation is one of the most powerful techniques currently available to the reservoir engineer upon which most reservoir development decisions rely on. According to the number of components used to describe the fluids there is an increasing demand for computational power due to the complexity and the iterative nature of the solution process. Phase stability and phase split computations often consume more than 50% of the simulation total CPU time as both problems need to be solved repeatedly and iteratively for each discretization block at each iteration of the non-linear solver. Therefore, speeding up these calculations is a research challenge of great interest. In this work, machine learning methods are proposed for the solving of the phase behavior problem. It is shown that under proper transformations, the unknown closed-form solution of the Equation-of-State based phase behavior formulation can be emulated by proxy models. The phase stability problem is treated by classifiers which label the fluid state in each block as either stable or unstable. For the phase split problem, regression models provide the prevailing equilibrium coefficients values given the feed composition, pressure and temperature. The development of these models is rapidly performed offline in an automated way, by utilizing the fluid tuned-EoS model prior to running the reservoir simulator. During the simulation run, rather than solving iteratively the phase behavior problem, the proxy models are called to provide non-iteratively direct answers at a constant, very small CPU charge regardless of the proximity to critical conditions. The proposed approach is presented in two-phase equilibria formulation but it can be extended to multi-phase equilibria applications. Examples demonstrate the advantages of this approach, the accuracy obtained in the calculations and the very significant CPU time reduction achieved with respect to conventional methods.
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Comparison and Validation of Theoretical and Empirical Correlations for Black Oil Reservoir Fluid Properties (SPE 152222)
Authors S. Godefroy, S.H. Khor and D. EmmsComparison and Validation of Theoretical and Empirical Correlations for Black Oil Reservoir Fluid Properties (SPE 152222)
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Application of Injection Fall-off Analysis in Polymer Flooding (SPE 154376)
Authors P. Van den Hoek, D. Brooks, H. Mahani, F. Saadi, S. Sen, K. Shuaili, T. Sorop and M. ZwaanDESCRIPTION Polymers exhibit non-Newtonian rheological behavior, such as in-situ shear-thinning and shear-thickening effects. This has a significant impact on pressure decline signature as exhibited during Pressure Fall-Off (PFO) tests. Therefore, applying a different PFO interpretation method, compared to conventional approaches for Newtonian fluids is required. RESULTS, OBSERVATIONS, CONCLUSIONS This paper presents a novel, simple and practical methodology to infer the in-situ polymer rheology from PFO tests performed during polymer injection. This is based on a combination of numerical flow simulations and analytical pressure transient calculations, resulting in generic type curves that are used to compute consistency index and flow behavior index, in addition to the usual reservoir parameters (kh, faulting, etc.) and parameters relating to (possible) induced fracturing during injection (fracture length and height). The tools and workflows are illustrated by a number of field examples of polymer PFO, which will also demonstrate how the polymer bank can be located from the data. APPLICATION This methodology can be used for interpretation of PFO tests on EOR polymer flooding projects, where monitoring of injection performance and of in-situ effective polymer rheology are key in the success of a project. SIGNIFICANCE OF SUBJECT MATTER The novelty of this study is that it presents a simple, straightforward methodology for analysis of polymer properties and polymer bank location from PFO tests which can be easily implemented into any software package. The methodology has a general applicability in that it also covers cases in which radial flow symmetry has been lost owing to induced fracturing during injection.
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Pressure Transient Analysis in Multiphase Multi Layer Reservoirs with Inter Layer Communication (SPE 152838)
Authors M. Mokhtari, A. Hashemi and E. NikjooThe focus of this study is on the investigation of multiphase flow effects on the pressure transient analysis in layered reservoirs with cross flow. Virtually all studies on the subject of multiphase well test analysis have been carried out in a single layer reservoirs. However, many reservoirs are found to be composed of number of layers whose characteristics are different from each other and the wells in such reservoirs may be completed and produced from more than one layer. A novel technique is presented by replacing multi-phase multi-layer reservoirs with cross flow with an equivalent single phase single layer reservoir. In order to investigate the applicability of the presented method several reservoirs in which the contrast in phase saturations in each layer is the parameter of interest is considered. The reservoir parameters such as phase mobilities, skin factor and average reservoir pressure are compared with actual values. According to the results of this work, it has been concluded that the reservoir parameters can be estimated by high accuracy with equivalent single phase single layer reservoir however, the data should be interpreted with care if horizontal saturation gradient is significant in the layers.
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Applications of Harmonic Pulse Testing to Field Cases (SPE 154048)
Authors P.A. Fokker and F. VergaHarmonic pulse testing is a well testing technique in which the injection or production rate is varied in a periodic way. The pressure response to the imposed rates, both in the pulser well and in the observer wells, can be analyzed in the frequency domain to evaluate the reservoir properties. The advantages of this type of test is that dedicated well testing surface equipment is not required and that the test can be performed during ongoing field operations. In an earlier study we demonstrated that the harmonic pulse testing methodology can be used to evaluate the development of effective permeability and total compressibility even for such a heterogeneous case as resulting from a water injection scenario. The analysis can be performed using a numerical simulator in the Fourier domain, by which heterogeneities can be explicitly taken into account. As time-stepping is not required in such a simulation, the calculation can be performed much faster. In the present paper we report on the application of the methodology to two field cases. In the first case a gas storage reservoir was operated with a day-night injection-shutin scenario. Data analysis could prove that the reservoir was homogeneous and that a minor fault identified by the seismic was not hindering hydraulic communication between the pulser and the observer wells. The second case was a harmonic test experiment in three groundwater wells which was reported earlier, but where the analysis was inadequate. The theory used was insufficient to consistently explain all the measurements, likely to be affected by strong reservoir heterogeneity. Only with our novel methodology it was possible to investigate the effects of heterogeneity. We demonstrate that a heterogeneity in the form of high-permeability streaks adequately describes the test results.
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Optimizing Well Placement with Quality Maps Derived From Multi-fidelity Meta-models (SPE 154416)
More LessThis paper presents a new methodology for locating infill wells so as to improve reservoir performance and value. The methodology centers on the determination of both qualitative and quantitative quality maps, quality being a measure of how good an area is expected to be for production. The determination of the best infill well locations is a highly nonlinear optimization problem. Solutions can be found using optimization algorithms. However, they usually correspond to local optima and require a few thousands of fluid flow simulations. This strongly penalizes the use of optimization algorithms for designing field production schemes. In this paper, we proposed a practical solution to handle infill well placement. First, various physical attributes are computed without any flow simulator to approximate the production capability of the reservoir. They are classified and used to delineate regions with poor or favorable potentials for well placement. Second, a few well locations are sampled on the basis of the defined regions and a flow simulation is performed for each of them to estimate how oil production evolves when an infill well is drilled at these locations. The resulting oil production responses are used to approximate oil production at unsampled locations. The specific feature of this method is to consider that grid blocks are characterized by their spatial coordinates plus the distance to the closest existing well. This third coordinate accounts for the wells already drilled and can be easily updated when a new one is implemented. This approach makes it possible to account for well interferences while calling for a reduced number of flow simulations. The proposed method is expedient. It does not yield the optimal locations of the wells to be added. Yet, it provides a useful first-pass set of well locations. An application case is presented to illustrate its potential.
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Complexity of Wettability Analysis in Heterogeneous Carbonate Rocks - A Case Study (SPE 154402)
Authors M. Mohammadlou and M.B. MorkEstimation of reservoir wettability and its effect on reservoir fluid flow, hydrocarbon recovery and fluid distribution has been the subject of many researches in recent years and remains one of the major challenges in reservoir characterization. This study examines the reservoir wettability in heterogeneous karstified carbonate rocks from comparison of special core analysis (SCAL) and resistivity index measurements on the core plugs, together with study of nuclear magnetic resonance (NMR) log, and formation pressure obtained by modular dynamic tool (MDT) measurements in the reservoir. The SCAL test results present moderately water-wet reservoir conditions at the cored intervals of the reservoir. Surveys from resistivity index measurements are in general agreement with the SCAL results. Due to lack of core data in the lower/main part of the reservoir, analysis of the NMR T2 distribution are combined with MDT data to describe the reservoir wettability. The pressure data suggests a water gradient through the reservoir column except for anomalous high pressure values in which corresponds to zones with high resistivity and oil saturations. High oil saturation is not expected in zones where the reservoir has been water flooded (water level rise in the reservoir) after hydrocarbon accumulation. The study of the T2 distribution of these intervals helps to identify the oil wet nature of the larger pores in the reservoir. The surface relaxivity of oil when it wets the pore surface cause a shift in the T2 distribution towards shorter T2sC". The water volume, then, in oil wet pores relaxes as bulk relaxation with longer T2 compared to the water wet case. This study suggest that a combination of the NMR log with MDT data and resistivity logs provides a method to identify wettability characteristics of complex rocks when core plugs are missing.
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