Browsing by Subject "Fast Marching Method"
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Item A Hierarchical History Matching Method and its Applications(2012-02-14) Yin, JichaoModern reservoir management typically involves simulations of geological models to predict future recovery estimates, providing the economic assessment of different field development strategies. Integrating reservoir data is a vital step in developing reliable reservoir performance models. Currently, most effective strategies for traditional manual history matching commonly follow a structured approach with a sequence of adjustments from global to regional parameters, followed by local changes in model properties. In contrast, many of the recent automatic history matching methods utilize parameter sensitivities or gradients to directly update the fine-scale reservoir properties, often ignoring geological inconsistency. Therefore, there is need for combining elements of all of these scales in a seamless manner. We present a hierarchical streamline-assisted history matching, with a framework of global-local updates. A probabilistic approach, consisting of design of experiments, response surface methodology and the genetic algorithm, is used to understand the uncertainty in the large-scale static and dynamic parameters. This global update step is followed by a streamline-based model calibration for high resolution reservoir heterogeneity. This local update step assimilates dynamic production data. We apply the genetic global calibration to unconventional shale gas reservoir specifically we include stimulated reservoir volume as a constraint term in the data integration to improve history matching and reduce prediction uncertainty. We introduce a novel approach for efficiently computing well drainage volumes for shale gas wells with multistage fractures and fracture clusters, and we will filter stochastic shale gas reservoir models by comparing the computed drainage volume with the measured SRV within specified confidence limits. Finally, we demonstrate the value of integrating downhole temperature measurements as coarse-scale constraint during streamline-based history matching of dynamic production data. We first derive coarse-scale permeability trends in the reservoir from temperature data. The coarse information are then downscaled into fine scale permeability by sequential Gaussian simulation with block kriging, and updated by local-scale streamline-based history matching. he power and utility of our approaches have been demonstrated using both synthetic and field examples.Item A Novel Approach for the Rapid Estimation of Drainage Volume, Pressure and Well Rates(2012-11-12) Gupta, Neha 1986-For effective reservoir management and production optimization, it is important to understand drained volumes, pressure depletion and reservoir well rates at all flow times. For conventional reservoirs, this behavior is based on the concepts of reservoir pressure and energy and convective flow. But, with the development of unconventional reservoirs, there is increased focus on the unsteady state transient flow behavior. For analyzing such flow behaviors, well test analysis concepts are commonly applied, based on the analytical solutions of the diffusivity equation. In this thesis, we have proposed a novel methodology for estimating the drainage volumes and utilizing it to obtain the pressure and flux at any location in the reservoir. The result is a semi-analytic calculation only, with close to the simplicity of an analytic approach, but with significantly more generality. The approach is significantly faster than a conventional finite difference solution, although with some simplifying assumptions. The proposed solution is generalized to handle heterogeneous reservoirs, complex well geometries and bounded and semi-bounded reservoirs. Therefore, this approach is particularly beneficial for unconventional reservoir development with multiple transverse fractured horizontal wells, where limited analytical solutions are available. To estimate the drainage volume, we have applied an asymptotic solution to the diffusivity equation and determined the diffusive time of flight distribution. For the pressure solution, a geometric approximation has been applied within the drainage volume to reduce the full solution of the diffusivity equation to a system of decoupled ordinary differential equations. Besides, this asymptotic expression can also be extended to obtain the well rates, producing under constant bottomhole pressure constraint. In this thesis, we have described the detailed methodology and its validation through various case studies. We have also studied the limits of validity of the approximation to better understand the general applicability. We expect that this approach will enable the inversion of field performance data for improved well and/or fracture characterization, and similarly, the optimization of well trajectories and fracture design, in an analogous manner to how rapid but approximate streamline techniques have been used for improved conventional reservoir management.Item Application of Fast Marching Method in Shale Gas Reservoir Model Calibration(2013-07-26) Yang, ChangdongUnconventional reservoirs are typically characterized by very low permeabilities, and thus, the pressure depletion from a producing well may not propagate far from the well during the life of a development. Currently, two approaches are widely utilized to perform unconventional reservoir analysis: analytical techniques, including the decline curve analysis and the pressure/rate transient analysis, and numerical simulation. The numerical simulation can rigorously account for complex well geometry and reservoir heterogeneity but also is time consuming. In this thesis, we propose and apply an efficient technique, fast marching method (FMM), to analyze the shale gas reservoirs. Our proposed approach stands midway between analytic techniques and numerical simulation. In contrast to analytical techniques, it takes into account complex well geometry and reservoir heterogeneity, and it is less time consuming compared to numerical simulation. The fast marching method can efficiently provide us with the solution of the pressure front propagation equation, which can be expressed as an Eikonal equation. Our approach is based on the generalization of the concept of depth of investigation. Its application to unconventional reservoirs can provide the understanding necessary to describe and optimize the interaction between complex multi-stage fractured wells, reservoir heterogeneity, drainage volumes, pressure depletion, and well rates. The proposed method allows rapid approximation of reservoir simulation results without resorting to detailed flow simulation, and also provides the time-evolution of the well drainage volume for visualization. Calibration of reservoir models to match historical dynamic data is necessary to increase confidence in simulation models and also minimize risks in decision making. In this thesis, we propose an integrated workflow: applying the genetic algorithm (GA) to calibrate the model parameters, and utilizing the fast marching based approach for forward simulation. This workflow takes advantages of both the derivative free characteristics of GA and the speed of FMM. In addition, we also provide a novel approach to incorporate the micro-seismic events (if available) into our history matching workflow so as to further constrain and better calibrate our models.Item Application of Fast Marching Methods for Rapid Reservoir Forecast and Uncertainty Quantification(2013-05-17) Olalotiti-Lawal, FeyisayoRapid economic evaluations of investment alternatives in the oil and gas industry are typically contingent on fast and credible evaluations of reservoir models to make future forecasts. It is often important to also quantify inherent risks and uncertainties in these evaluations. These ideally require several full-scale numerical simulations which is time consuming, impractical, if not impossible to do with conventional (Finite Difference) simulators in real life situations. In this research, the aim will be to improve on the efficiencies associated with these tasks. This involved exploring the applications of Fast Marching Methods (FMM) in both conventional and unconventional reservoir characterization problems. In this work, we first applied the FMM for rapidly ranking multiple equi-probable geologic models. We demonstrated the suitability of drainage volume, efficiently calculated using FMM, as a surrogate parameter for field-wide cumulative oil production (FOPT). The probability distribution function (PDF) of the surrogate parameter was point-discretized to obtain 3 representative models for full simulations. Using the results from the simulations, the PDF of the reservoir performance parameter was constructed. Also, we investigated the applicability of a higher-order-moment-preserving approach which resulted in better uncertainty quantification over the traditional model selection methods. Next we applied the FMM for a hydraulically fractured tight oil reservoir model calibration problem. We specifically applied the FMM geometric pressure approximation as a proxy for rapidly evaluating model proposals in a two-stage Markov Chain Monte Carlo (MCMC) algorithm. Here, we demonstrated the FMM-based proxy as a suitable proxy for evaluating model proposals. We obtained results showing a significant improvement in the efficiency compared to conventional single stage MCMC algorithm. Also in this work, we investigated the possibility of enhancing the computational efficiency for calculating the pressure field for both conventional and unconventional reservoirs using FMM. Good approximations of the steady state pressure distributions were obtained for homogeneous conventional waterflood systems. In unconventional system, we also recorded slight improvement in computational efficiency using FMM pressure approximations as initial guess in pressure solvers.Item Fast Marching Method with Multiphase Flow and Compositional Effects(2014-08-06) Fujita, YusukeIn current petroleum industry, there is a lack of effective reservoir simulators for modeling shale and tight sand reservoirs. An unconventional resource modeling requires an accurate flow characterization of complex transport mechanisms caused by the interactions among fractures, inorganic matrices, and organic rocks. Pore size in shale and tight sand reservoirs typically ranges in nanometers, which results in ultralow permeability (nanodarcies) and a high capillary pressure in the confined space. In such extremely low permeability reservoirs, adsorption/desorption and diffusive flow processes play important roles for a fluid flow behavior in addition to heterogeneity-driven convective flow. In this study, the concept of ?Diffusive Time of Flight? (DTOF) is generalized for multiphase and multicomponent flow problems on the basis of the asymptotic theory. The proposed approach consists of two decoupled steps ? (1) calculation of well drainage volumes along a propagating ?peak? pressure front, and (2) numerical simulation based on the transformed 1-D coordinates. Geological heterogeneities distributed in 3-D space are integrated by tracking the propagation of ?peak? pressure front using a ?Fast Marching Method? (FMM), and subsequently, the drainage volumes are evaluated along the outwardly propagation contours. A DTOF-based numerical simulation is performed by treating a series of the DTOF as a spatial coordinate. This approach is analogous to streamline simulation, whereby a multidimensional simulation is transformed into 1-D coordinates resulting in substantial savings in computational time, thus allowing for high resolution simulation. However, instead of using a convective time of flight (CTOF), a diffusive time of flight is introduced in the modeling of a pressure front propagation. The overall workflow, which consist of the FMM and numerical simulation, is described in detail for single-phase, two-phase, blackoil, and compositional cases. The model validation is firstly performed on single-porosity systems with and without geological heterogeneity, then extended to multi-continuum domains including dual-porosity fractured reservoir and triple-continuum system. The large-scale unconventional models are finally demonstrated in consideration of the permeability correction for shale gas system and capillarity incorporation for confined phase behavior in multiphase shale oil system.