A thesis Submitted to the School of Chemical and Metallurgical Engineering, Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in fulfillment of the requirements for the degree of Doctor of Philosophy Johannesburg, 2016 / Wettability of a porous reservoir rock is an important factor that affects oil recovery during waterflooding. It is recognized as being important for multiphase properties. Understanding the variation of these properties in the field, due to wettability trends and different pore structures, is very critical for designing efficient and reliable processes and projects for enhanced hydrocarbon recovery. After primary drainage the reservoir wettability changes: if it was oil-wet initially, it gradually changes to water-wet during waterflooding. This change in reservoir wettability towards water-wet will reduce the residual oil saturation and improve the oil displacement efficiency. However, knowledge of the constitutive relationship between the pore scale descriptors of transport in the porous system is required to adequately describe wettability trend and its impact on oil recovery, particularly during waterflooding. In this work, the petrophysical properties that define fluid flow in the Agbada, Nigeria sandstone reservoir were determined using conventional experimental and x-ray CT scanning methods. Experimentally measured average porosity is 0.28, average permeability is 1699 mD, while the initial and irreducible water saturation is 0.22. Permeability in the x, y and z directions, ranging from 50 to 200 mD, were calculated from the pore network extracted from the Agbada sandstone rock. Results obtained from the Amott-Harvey wettability measurement method indicate that the reservoir is strongly water-wet, with Amott-Harvey index of about 0.9. The cross-over between the water and oil relative permeabilities occurred at saturations of the samples above 0.5, giving an indication of strong water-wetness. The work summarizes the mechanism of wettability alteration and characterizes the performance of the reservoir during waterflooding from injecting water, and relates the residual oil saturation, relative permeability and volumes of water injected to wettability and its effects on oil recovery. Waterflood oil recovery is computed using the Buckley-Leverett method based on the reservoir rock and fluid properties. Computed waterflood oil recovery using this method was about 60% of the oil initially in place. Plots of spontaneous imbibition rate show that the injection rate for optimal oil recovery is 40 bbls of injected water per day. At this rate, both the mobility and shock front mobility ratios are less than 1, leading to a stable flood front and absence of viscous fingering. Waterflooding is by far the most widely applied method of improved oil recovery over the years with good results in conventional and unconventional (tight oil) reservoirs It is relatively simple and cost effective: abundance and availability of water. Waterflood oil recovery factor is affected by internal and external factors. The placement of the injection and production wells, for example, impacts on the effectiveness of the waterflooding process. I considered the placement of the wells in a five-spot pattern as elements of an unbounded double periodic array of wells and assumed the reservoir to be homogeneous, infinite and isotropic, with constant porosity and permeability. Both fluids are treated as having slight but constant compressibility and their flow governed by Darcy’s law. The average pressure in the reservoir satisfies quasi-static flow or diffusion equation. I then assumed piston-like displacement of oil by injected water that takes account of viscosity diffence between both fluids and proposed a model based on the theory of elliptic functions, in particular Weierstrass p-functions functions. Oil-water contact movement, dimensionless time for water breakthrough at the production well, areal sweep and average reservoir pressures were modeled. The model was tested using Wolfram Mathematica 10 software and the results are promising. The thesis has therefore established that the Agbada sandstone reservoir is strongly water-wet and that waterflooding is a viable option for enhanced oil recovery from the reservoir. / MT2016

Thesis (Ph. D.)--University of Wyoming, 2006. / Title from PDF title page (viewed on Dec. 21, 2007). Includes bibliographical references (p. 199-216).

Thesis (M.Eng.)--Memorial University of Newfoundland, 2005. / Bibliography: leaves 130-135.

Unconventional reservoir systems can best be described as petroleum (oil and/or gas) accumulations which are difficult to be characterized and produced by conventional technologies. In this work we present the development of a systematic procedure to evaluate well performance in unconventional (i.e., low to ultra-low permeability) reservoir systems. The specific tasks achieved in this work include the following: ● Integrated Diagnostics and Analysis of Production Data in Unconventional Reservoirs: We identify the challenges and common pitfalls of production analysis and provide guidelines for the analysis of production data. We provide a comprehensive workflow which consists of model-based production analysis (i.e., rate-transient or model matching approaches) complemented by traditional decline curve analysis to estimate reserves in unconventional reservoirs. In particular, we use analytical solutions (e.g., elliptical flow, horizontal well with multiple fractures solution, etc.) which are applicable to wells produced in unconventional reservoirs. ● Deconvolution: We propose to use deconvolution to identify the correlation between pressure and rate data. For our purposes we modify the B-spline deconvolution algorithm to obtain the constantpressure rate solution using cumulative production and bottomhole pressure data in real time domain. It is shown that constant-pressure rate and constant-rate pressure solutions obtained by deconvolution could identify the correlation between measured rate and pressure data when used in conjunction. ● Series of Rate-Time Relations: We develop three new main rate-time relations and five supplementary rate-time relations which utilize power-law, hyperbolic, stretched exponential, and exponential components to properly model the behavior of a given set of rate-time data. These relations are well-suited for the estimation of ultimate recovery as well as for extrapolating production into the future. While our proposed models can be used for any system, we provide application almost exclusively for wells completed in unconventional reservoirs as a means of providing estimates of time-dependent reserves. We attempt to correlate the rate-time relation model parameters versus model-based production analysis results. As example applications, we present a variety of field examples using production data acquired from tight gas, shale gas reservoir systems.

Thesis (M.S.)--West Virginia University, 2001. / Title from document title page. Document formatted into pages; contains xi, 149 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 118-124).

Chemical flooding is one of the most difficult enhanced oil recovery methods and was considered a high-risk process in the past. Some reasons are low and uncertain oil price, high chemical prices, lack of confidence in performance of the chemical flooding process, long project life, and reservoir and process uncertainties. However, with significant improvement in simulation and optimization tools and high oil price, chemical flooding is feasible in terms of economical and carefully implemented design. Optimization of chemical floods requires complex integration of reservoir, chemical, economics properties and also drilling and production strategies. Many of these variables are uncertain parameters and many simulations are required to capture the effect of the uncertain and decision variables. These simulations could become very expensive and may not be feasible to consider all of the required simulation models. The goal of this research is the development of a methodology for optimization and design of chemical flooding of candidate oil reservoirs. We performed a comprehensive sensitivity study of reservoir and fluid properties that have significant influence on the oil production during the chemical flooding by performing a series of reservoir simulation runs. For performing the reservoir simulation runs, this study used the UT_IRSP platform and the multiphase, multicomponent, chemical flooding simulator called UTCHEM. During the study, UT_IRSP and UTCHEM have been modified by adding new modules, functions and variables. For example, a deviated well module was implemented in UTCHEM to study deviated wells. Deviated well module allows the users to introduce deviated wells in reservoir and import the well locations similar to Eclipse or CMG simulators. A time-dependent well schedule module was implemented in the UT_IRSP framework. This enhancement allows the well placement optimization studies to find the best time to add new wells, and change the status of the well for example from a producer to an injector in order to have an optimum development plan. An advanced post processing module was added to UT_IRSP in order to design, screen, and optimize complex cases for chemical enhanced oil recovery processes such as investigating the well patterns, well spacing, and type of the well (horizontal vs. vertical wells). An experimental design and response surface methodology with integrated economic model were utilized in this study to obtain the optimum design under uncertainties and have an optimal combination of the decision variables. This methodology is based on applying multi-regression analysis and ANOVA (analysis of variance) between the objective function (i.e. dependent variable, which is net present value (NPV) in chemical flooding) and other uncertain and process variables (independent variables). The economic analysis model used the discounted cash flow method to calculate net present value at the economic life of process, internal rate of return, and growth rate of return for each simulation case. Also the optimizer, OptQuest, is launched with a goal of maximizing the mean NPV. The range and the risk associated with the optimum design was studied using Monte Carlo simulation of objective function of the response variable and other independent variables. This methodology was applied for complex chemical flood cases such as well placement, change of status of wells as a function of time or well pattern and well spacing to investigate the best well scenario from recovery and economics point of view. / text

The Capacitance Resistance Model (CRM) is a reservoir model based on a data-driven approach. It stems from the continuity equation and takes advantage of the usually abundant rate data to achieve a synergy of analytical model and data-driven approach. Minimal information (rates and bottom-hole pressure) is required to inexpensively characterize the reservoir. Important information, such as inter-well connectivity, reservoir compressibility effects, etc., can be easily and readily evaluated. The model also suggests optimal injection schemes in an effort to maximize ultimate oil recovery, and hence can assist real time reservoir analysis to make more informed management decisions. Nevertheless, an important limitation in the current CRM model is that it only treats the reservoir flow as single-phase flow, which does not favor capturing physics when the saturation change is large, such as for an immature water flood. To overcome this limitation, we develop a two-phase flow coupled CRM model that couples the pressure equation (fluid continuity equation) and the saturation equation (oil mass balance). Through this coupling, the model parameters such as the connectivity, the time constant, temporal oil saturation, etc., are estimated using nonlinear multivariate regression to history match historical production data. Incorporating the physics of two-phase displacement brings several advantages and benefits to the CRM model, such as the estimation of total mobility change, more accurate prediction of oil production, broader model application range, and better adaptability to complicated field scenarios. Also, the estimated saturation within the drainage volume of each producer can provide insights with respect to the field remaining oil saturation distribution. Synthetic field case studies are carried out to demonstrate the different capabilities of the coupled CRM model in homogeneous and heterogeneous reservoirs with different geological features. The physical meanings of model parameters are well explained and validated through case studies. The results validate the coupled CRM model and show improved accuracy in model parameters obtained through the history match. The prediction of oil production is also significantly improved compared to the current CRM model. A more reliable oil rate prediction enables further optimization to adjust injection strategies. The coupled CRM model has been shown to be fast and stable. Moreover, sensitivity analyses are conducted to study and understand the impact of the input information (e.g., relative permeability, viscosity) upon the output model parameters (e.g., connectivity, time constants). This analysis also proves that the model parameters from the two-phase coupled model can combine both reservoir compressibility and mobility effects. / text

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Thesis (Ph. D.)--University of Wyoming, 2005. / Title from PDF title page (viewed on Nov. 1, 2007). Includes bibliographical references (p. 179-192).

Thesis (Ph.D.)--University of Tulsa, 1993. / Includes bibliographical references (leaves 240-250).