# Browsing by Subject "Proxy"

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Item A history matching workflow using proxy-based MCMC applied in tight reservoir simulation studies(2017-09-15) Dachanuwattana, Silpakorn; Sepehrnoori, Kamy, 1951-Show more Reservoir simulation for tight reservoirs often requires characterization of hydraulic and natural fracture networks in the reservoir model. Microseismic data reveals approximate boundary of the fracture networks but its direct application of stimulated rock volume (SRV) fails short to capture fracture connectivity and fracture conductivity, which significantly dominate well performance. Embedding discrete fractures in reservoir simulation is thus required to attain more realistic reservoir behavior. However, using local grid refinement (LGR) to model discrete fractures is computationally expensive. Even more challenging is generating multiple realizations of the fracture-embedded reservoir models during history-matching. Not only one simulation but extensive series of simulations are required to deal with complex geometry of fractures as well as other uncertain parameters. However, recent developments in a methodology called Embedded Discrete Fracture Model (EDFM) have overcome the computational complexity using discrete fractures in reservoir simulations. In this thesis, we develop an efficient assisted history matching (AHM) workflow using proxy-based Markov chain Monte Carlo (MCMC) algorithm and integrate the workflow with the EDFM preprocessor. To improve the efficiency, the optimal proxy is studied by comparing the performance of four types of proxies: quadratic polynomial, cubic polynomial, k-nearest neighboring (KNN), and kriging under various contexts such as different measurement errors. The results show that kriging proxy is more accurate than KNN proxy and cubic proxy. The quadratic proxy was the least accurate in our evaluations. However, if larger measurement error is introduced, the distinction between accuracy of the four proxies becomes less clear in spite of their different computational costs. Incorporating these findings, the proxy-based MCMC workflow is developed and implemented in conjunction with the EDFM to history match a shale oil well in Vaca Muerta formation to demonstrate the application of the workflow. The microseismic data are accounted to constrain the uncertain geometries of the fractures. The integrated workflow can successfully and efficiently history match the actual shale-oil well with complex fractures. Not only the uncertainties of reservoir properties are narrowed down but the posterior likelihood of fracture geometry scenario is also attained after history matching. We also compare the proxy-based MCMC workflow with the direct MCMC and a commercial history matching software in terms of accuracy and efficiency. It is found that the direct MCMC cannot find enough solutions to construct the posterior probability density (PPD) in an efficient manner. For the commercial software, it can find solutions faster than the proxy-based MCMC. However, the former is stuck in the local minima, thus resulting in an invalid PPD. Ultimately, the proxy-based MCMC workflow provides the most accurate history matching results with efficient manner for this tight oil reservoir.Show more Item Assisted history matching workflow for unconventional reservoirs(2019-05-13) Tripoppoom, Sutthaporn; Sepehrnoori, Kamy, 1951-Show more The information of fractures geometry and reservoir properties can be retrieved from the production data, which is always available at no additional cost. However, in unconventional reservoirs, it is insufficient to obtain only one realization because the non-uniqueness of history matching and subsurface uncertainties cannot be captured. Therefore, the objective of this study is to obtain multiple realizations in shale reservoirs by adopting Assisted History Matching (AHM). We used multiple proxy-based Markov Chain Monte Carlo (MCMC) algorithm and Embedded Discrete Fracture Model (EDFM) to perform AHM. The reason is that MCMC has benefits of quantifying uncertainty without bias or being trapped in any local minima. Also, using MCMC with proxy model unlocks the limitation of an infeasible number of simulations required by a traditional MCMC algorithm. For fractures modeling, EDFM can mimic fractures flow behavior with a higher computational efficiency than a traditional local grid refinement (LGR) method and more accuracy than the continuum approach. We applied the AHM workflow to actual shale gas wells. We found that the algorithm can find multiple history matching solutions and quantify the fractures and reservoir properties posterior distributions. Then, we predicted the production probabilistically. Moreover, we investigated the performance of neural network (NN) and k-nearest neighbors (KNN) as a proxy model in the proxy-based MCMC algorithm. We found that NN performed better in term of accuracy than KNN but NN required twice running time of KNN. Lastly, we studied the effect of enhanced permeability area (EPA) and natural fractures existence on the history matching solutions and production forecast. We concluded that we would over-predict fracture geometries and properties and estimated ultimate recovery (EUR) if we assumed no EPA or no natural fractures even though they actually existed. The degree of over-prediction depends on fractures and reservoir properties, EPA and natural fractures properties, which can only be quantified after performing AHM. The benefits from this study are that we can characterize fractures geometry, reservoir properties, and natural fractures in a probabilistic manner. These multiple realizations can be further used for a probabilistic production forecast, future fracturing design improvement, and infill well placement decision.Show more Item Fast assessment of uncertainty in buoyant fluid displacement using a connectivity-based proxy(2016-05) Jeong, Hoonyoung; Sepehrnoori, Kamy, 1951-; Srinivasan, Sanjay; Wheeler, Mary; Delshad, Mojdeh; Sen, MrinalShow more It is crucial to estimate the uncertainty in flow characteristics of injected fluid. However, because a large suite of geological models is probable given sparse static data, it is impractical to conduct full physics flow simulations on the entire suite of models in order to quantify the uncertainty in fluid displacements. Thus a fast alternative to a full physics simulator is necessary to quickly predict the fluid displacements. Most of the proxies proposed thus far are inappropriate to approximate the buoyant flow of injected fluid for 3D heterogeneous rock during the injection period. In this dissertation, a new proxy will be proposed to quickly predict the buoyant flow of injected fluid during CO2 sequestration. The geological models are ranked based on the extent of the approximated CO2 plumes. By selecting a representative group of models among the ranked models, the uncertainty in the spatial and temporal characteristics of the CO2 plume migrations can be quickly quantified. About 90% of the computational cost of quantifying the uncertainty in the extent of CO2 plumes was saved using the proposed connectivity based proxy. In a geological carbon storage project, the spatial and temporal characteristics of CO2 plume migrations can be monitored by 4D seismic surveys. The images of CO2 plumes obtained from 4D seismic surveys are used as observed data to find subsurface models honoring the spatial and temporal characteristics of the observed CO2 plumes. However, because manually comparing an observed CO2 plume and prior CO2 plumes in a large suite of subsurface models is inefficient, an automatic measure to calculate the dissimilarity between the CO2 plumes is necessary. The most intuitive way to calculate the dissimilarity is the Euclidean distance between vectors representing CO2 plumes. However, this is inappropriate to measure the dissimilarity between CO2 plumes because it does not consider spatial relation between the elements of the vectors. The shape dissimilarity between the CO2 plumes that reflects the spatial relation can be calculated using the Hausdorff distance. The computational cost of calculating the shape dissimilarity between CO2 plumes is significantly reduced by calculating the Hausdorff distance between the representations of the CO2 plumes such as perimeter, surface, and skeleton instead of the original CO2 plumes. An appropriate representation should be chosen according to the spatial characteristics of CO2 plumes.Show more