The current streamline formulation is limited to single-porosity systems and is then not suitable for application to naturally fractured reservoirs. Describing the fluid transport in naturally fractured reservoirs has been recognized as a main challenge for simulation engineers due to the complicated physics involved. In this work, we generalized the streamline-based simulation to describe the fluid transport in naturally fractured reservoirs. We implemented three types of transfer function: the conventional transfer function (CTF), the diffusion transfer function (DTF), and the empirical transfer function (ETF). We showed that these transfer functions can be implemented easily in the current single-porosity streamline codes. These transfer functions have been added as a source term to the transport equation that describes the saturation evolution along the streamlines. We solved this equation numerically for all types of transfer functions. The numerical solution of the continuity equation with DTF and ETF requires discretizing a convolution term. We derived an analytical solution to the saturation equation with ETF in terms of streamline TOF to validate the numerical solution. We obtain an excellent match between the numerical and the analytical solution. The final stage of our study was to validate our work by comparing our dual-porosity streamline simulator (DPSS) to the commercial dual-porosity simulator, ECLIPSE. The dual-porosity ECLIPSE uses the CTF to describe the interaction between the matrix-blocks and the fracture system. The dual-porosity streamline simulator with CTF showed an excellent match with the dual-porosity ECLIPSE. On the other hand, dual-porosity streamline simulation with DTF and ETF showed a lower recovery than the recovery obtained from the dual-porosity ECLIPSE and the DPSS with CTF. This difference in oil recovery is not due to our formulation, but is related to the theoretical basis on which CTF, DTF, and ETF were derived in the literature. It was beyond the scope of this study to investigate the relative accuracy of each transfer function. We demonstrate that the DPSS is computationally efficient and ideal for large-scale field application. Also, we showed that the DPSS minimizes numerical smearing and grid orientation effects compared to the dual-porosity ECLIPSE.

After field redevelopment in the Sherrod Unit of the Spraberry Trend Area, an inter-well tracer test was conducted at the field scale in order to understand the fracture system, which forms preferential flow paths for better management of waterflooding. The test consisted of 13 injection wells and more than 110 producing wells that were sampled, with each injector having its own unique tracer. A wide range of tracer responses was observed in terms of tracer recovery, breakthrough time, and tracer velocity. Additional noise on tracer data was noticed due to reinjection of produced water. In this study, a comprehensive workflow is presented for dynamic reservoir characterization of naturally fractured reservoirs from an inter-well tracer test by incorporation of analytical interpretation, streamline simulation, and streamline-based optimization techniques. Categorized tracer responses were mapped according to analytical analysis, and dominating flow trends were detected in E-W and NE-SW directions before the simulation study. The constructed three-phase, dual-porosity model was simulated by a streamline simulator. Certain parameters in the model were modified based on high tracer response until a reasonable match was obtained for an inverted nine-spot pattern and breakthrough time of the injected tracer. Once the model became capable of matching historical field production, a 1-year prediction run was conducted for optimization. Cumulative oil production was increased by 8,000 bbl by allocating more water toward efficient producers, and 10,000 bbl less water was produced for the optimized case. The electronic version of this dissertation is accessible from http://hdl.handle.net/1969.1/151965

Low Salinity and Engineered Water Injection for Sandstone and Carbonate Reservoirs provides a first of its kind review of the low salinity and engineered water injection (LSWI/EWI) techniques for today’s more complex enhanced oil recovery methods. Reservoir engineers today are challenged in the design and physical mechanisms behind low salinity injection projects, and to date, the research is currently only located in numerous journal locations. This reference helps readers overcome these challenging issues with explanations on models, experiments, mechanism analysis, and field applications involved in low salinity and engineered water. Covering significant laboratory, numerical, and field studies, lessons learned are also highlighted along with key areas for future research in this fast-growing area of the oil and gas industry. After an introduction to its techniques, the initial chapters review the main experimental findings and explore the mechanisms behind the impact of LSWI/EWI on oil recovery. The book then moves on to the critical area of modeling and simulation, discusses the geochemistry of LSWI/EWI processes, and applications of LSWI/EWI techniques in the field, including the authors’ own recommendations based on their extensive experience. It is an essential reference for professional reservoir and field engineers, researchers and students working on LSWI/EWI and seeking to apply these methods for increased oil recovery. Teaches users how to understand the various mechanisms contributing to incremental oil recovery using low salinity and engineering water injection (LSWI/EWI) in sandstones and carbonates Balances guidance between designing laboratory experiments, to applying the LSWI/EWI techniques at both pilot-scale and full-field-scale for real-world operations Presents state-of-the-art approaches to simulation and modeling of LSWI/EWI

We explore the use of efficient streamline-based simulation approaches for modeling and analysis partitioning interwell tracer tests in heterogeneous and fractured hydrocarbon reservoirs. The streamline approach is generalized to model water injection in naturally fractured reservoirs through the use of a dual media approach. The fractures and matrix are treated as separate continua that are connected through a transfer function, as in conventional finite difference simulators for modeling fractured systems. A detailed comparison with a commercial finite difference simulator shows very good agreement. Furthermore, an examination of the scaling behavior of the computation time indicates that the streamline approach is likely to result in significant savings for large-scale field applications. We also propose a novel approach to history matching finite-difference models that combines the advantage of the streamline models with the versatility of finite-difference simulation. In our approach, we utilize the streamline-derived sensitivities to facilitate history matching during finite-difference simulation. The use of finite-difference model allows us to account for detailed process physics and compressibility effects. The approach is very fast and avoids much of the subjective judgments and time-consuming trial-and-errors associated with manual history matching. We demonstrate the power and utility of our approach using a synthetic example and two field examples. Finally, we discuss several alternative ways of using partitioning interwell tracer tests (PITTs) in oil fields for the calculation of oil saturation, swept pore volume and sweep efficiency, and assess the accuracy of such tests under a variety of reservoir conditions.

The conventional and modern well test interpretation methods are an important tool in the petroleum engineer’s toolkit. Used in the exploration and discovery phase of a field, they are performed to determine the quality of a well or to permit estimation of producing rates at different producing pressures. However once a field enters the middle and later development phase, the reservoir flow environment grows increasingly complex and conventional or modern methods do not satisfy the needs of old field development and evaluation. Based on over 10 years of field and research experience, Streamline Numerical Well Test Interpretation Theory and Method provides an effective method for the determination of residual oil distribution for the middle and mature phases of a field. One of the most advanced books available, the author explains the development history of well test theory, analyzes the limitation of modern well test interpretation method, and proposes the concept and framework of numerical well test. This is quickly followed by an introduction of basic principles and solution procedures of streamline numerical simulation theory and method. The book then systematically applies streamline numerical well test interpretation models to a multitude of reservoir types, ranging from single layer reservoir to multi-layer reservoirs. The book presents multi-parameter streamline numerical well test automatic match interpretation method based on double-population genetic algorithm, which lays the foundation to fast automatic match of numerical well test. The book introduces streamline numerical well test interpretation software with independent intellectual property right which is programmed based on the above theoretical studies. Single and muti-layer sandstone water flooding reservoirs Multi-layer sandstone chemical flooding model and components Explains the application of streamline numerical well test and software Applies programmed software to 177 wells Quickly calculate the distribution of pressure, saturation and streamline Covers all kinds of numerical well test interpretation models Avoid the disadvantages of conventional well test and numerical well test interpretation method Complete tutorial on streamline numerical well test interpretation software

Streamline-based models have shown great potential in reconciling high resolution geologic models to production data. In this work we extend the streamline-based production data integration technique to naturally fractured reservoirs. We use a dual-porosity streamline model for fracture flow simulation by treating the fracture and matrix as separate continua that are connected through a transfer function. Next, we analyticallycompute the sensitivities that define the relationship between the reservoir properties and the production response in fractured reservoirs. Finally, production data integration is carried out via the Generalized Travel Time inversion (GTT). We also apply the streamline-derived sensitivities in conjunction with a dual porosity finite difference simulator to combine the efficiency of the streamline approach with the versatility of the finite difference approach. This significantly broadens the applicability of the streamline- based approach in terms of incorporating compressibility effects and complex physics. The number of reservoir parameters to be estimated is commonly orders of magnitude larger than the observation data, leading to non-uniqueness and uncertainty in reservoir parameter estimate. Such uncertainty is passed to reservoir response forecast which needs to be quantified in economic and operational risk analysis. In this work we sample parameter uncertainty using a new two-stage Markov Chain Monte Carlo (MCMC) that is very fast and overcomes much of its current limitations. The computational efficiency comes through a substantial increase in the acceptance rate during MCMC by using a fast linearized approximation to the flow simulation and the likelihood function, the critical link between the reservoir model and production data. The Gradual Deformation Method (GDM) provides a useful framework to preserve geologic structure. Current dynamic data integration methods using GDM are inefficient due to the use of numerical sensitivity calculations which limits the method to deforming two or three models at a time. In this work, we derived streamline-based analytical sensitivities for the GDM that can be obtained from a single simulation run for any number of basis models. The new Generalized Travel Time GDM (GTT-GDM) is highly efficient and achieved a performance close to regular GTT inversion while preserving the geologic structure.