The demand for oil and gas is increasing yearly, whereas proven oil and gas reserves are being depleted. The potential of stripper oil and gas fields to supplement the national energy supply is large. In 2006, stripper wells accounted for 15% and 8% of US oil and gas production, respectively. With increasing energy demand and current high oil and gas prices, integrated reservoir studies, secondary and tertiary recovery methods, and infill drilling are becoming more common as operators strive to increase recovery from stripper oil and gas fields. The primary objective of this research was to support optimized production of oil and gas from stripper well fields by evaluating one stripper gas field and one stripper oil field. For the stripper gas field, I integrated geologic and engineering data to build a detailed reservoir characterization model of the Second White Specks (SSPK) reservoir in Garden Plains field, Alberta, Canada. The objectives of this model were to provide insights to controls on gas production and to validate a simulation-based method of infill drilling assessment. SSPK was subdivided into Units A ? D using well-log facies. Units A and B are the main producing units. Unit A has better reservoir quality and lateral continuity than Unit B. Gas production is related primarily to porosity-netthickness product and permeability and secondarily to structural position, minor structural features, and initial reservoir pressure. For the stripper oil field, I evaluated the Green River formation in the Wells Draw area of Monument Butte field, Utah, to determine interwell connectivity and to assess optimal recovery strategies. A 3D geostatistical model was built, and geological realizations were ranked using production history matching with streamline simulation. Interwell connectivity was demonstrated for only major sands and it increases as well spacing decreases. Overall connectivity is low for the 22 reservoir zones in the study area. A water-flood-only strategy provides more oil recovery than a primary-then-waterflood strategy over the life of the field. For new development areas, water flooding or converting producers to injectors should start within 6 months of initial production. Infill drilling may effectively produce unswept oil and double oil recovery. CO2 injection is much more efficient than N2 and CH4 injection. Water-alternating-CO2 injection is superior to continuous CO2 injection in oil recovery. The results of this study can be used to optimize production from Garden Plains and Monument Butte fields. Moreover, these results should be applicable to similar stripper gas and oil field fields. Together, the two studies demonstrate the utility of integrated reservoir studies (from geology to engineering) for improving oil and gas recovery.

Pressure drawdown tests were conducted using Schlumberger’s Modular Formation Dynamics Tester™ (MDT) wireline tool in the Mallik methane hydrate (MH) reservoirs in February 2002 as well as in the Mount Elbert (Alaska) MH reservoirs in February 2007, while a production test was conducted applying a depressurization method in one of the Mallik MH reservoirs in April 2007. All of these tests aimed at measuring production and bottomhole pressure (BHP) responses by reducing BHP below the MH stability pressure to estimate reservoir properties such as permeability and MH dissociation radius. We attempted to analyze the results of these tests through history matching using the numerical simulator (MH21-HYDRES) coded especially for gas hydrate reservoirs. Although the magnitude of depressurization and the total duration spent for these tests were almost identical to each other, the simulation studies revealed that there existed significant differences in what could be inferred and could not be inferred from test results between a MDT test and a production test. The simulation studies mainly clarified that (1) the MDT tests were useful to estimate initial effective permeability in the presence of MH, (2) when BHP is reduced below the MH stability pressure at MDT tests, the pressure and temperature responses were significantly influenced by the wellbore storage erasing all the important data such as those indicating a radius of MH dissociation and effective permeability after partial MH dissociation, and (3) history matching of production tests tended to result in multiple solutions unless establishing steady flow conditions. This paper presents the results of history matching for the typical MDT and production tests conducted in Mallik and Alaska MH reservoirs. This paper also discusses the parameters reliably estimated through MDT and production tests, which should provide many suggestions on future designs and analyses of short-term tests for MH reservoirs.

A gas hydrate production test using the depressurization method was conducted in early April 2007 as part of the JOGMEC/NRCan/Aurora Mallik production research program. The results of the production test were analyzed using a numerical simulator (MH21-HYDRES) coded especially for gas hydrate reservoirs. This paper evaluates the test results based on analyses of production test data, numerical modeling and a series of history matching simulations. Methane gas and water was produced from a 12 m perforation interval within one of the major methane hydrate (MH) reservoirs at the Mallik MH field, by reducing the bottomhole pressure down to about 7 MPa. The measured gas production rate was far higher than that expected for a comparatively small pressure drawdown. However, irregular (on-off) pumping operations, probably related to excessive sand production, resulted in unstable fluid flow within the wellbore, which made the analysis of test performance extremely complicated. A numerical reservoir model was constructed as a series of grid blocks, including those mimicking the wellbore, to enable rigorous simulation of fluid flow patterns in the vicinity of the wellbore. The model was then tuned through history matching, not by simply adjusting reservoir parameters, but by introducing the concept that sand production might have dramatically increased the near-wellbore permeability. The good agreement between observed and simulated performances suggests the mechanism of MH dissociation/production during the test. The history matched reservoir model was employed to predict the second-year production test performance, in order to examine the gas production potential of the Mallik MH reservoir, and to provide insight into future exploration and development planning for MH reservoirs.

Unconventional 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.

No description available.

For a natural gas importing country, &ldquo / take or pay&rdquo / approach creates problems since the demand for natural gas varies during the year and the excess amount of natural gas should be stored. In this study, an underground gas storage project is evaluated in a depleted gas Field M. After gathering all necessary reservoir, fluid, production and pressure data, the data were adapted to computer language, which was used in a commercial simulator software (IMEX) that is the CMG&rsquo / s (Computer Modelling Group) new generation adoptive simulator, to reach the history matching. The history matching which consists of the 4 year of production of the gas reservoir is the first step of this study. The simulation program was able to accomplish a good history match with the given parameters of the reservoir. Using the history match as a base, five different scenarios were created and forecast the injection and withdrawal performance of the reservoir. These scenarios includes 5 newly drilled horizontal wells which were used in combinations with the existing wells. With a predetermined injection rate of 13 MMcf/D was set for all the wells and among the 5 scenarios, 5 horizontal &ndash / 6 vertical injectors &amp / 5 horizontal - 6 vertical producers is the most successful in handling the gas inventory and the time it takes for a gas injection and production period. After the determination of the well configuration, the optimum injection rate for the entire field was obtained and found to be 130 MMcf/D by running different injection rates for all wells and then for only horizontal wells different injection rates were applied with a constant injection rate of 130 MMcf/d for vertical wells. Then it has been found that it is better to apply the 5th scenario which includes 5 horizontal &ndash / 6 vertical injectors &amp / 5 horizontal - 6 vertical producers having an injection rate of 130 MMcf/d for horizontal and vertical wells. Since within the 5th scenario, changing the injection rate to 1.3 Bcf/d and 13 Bcf/d, did not effect and change the average reservoir pressure significantly, it is best to carry out the project with the optimum injection rate which is 130 MMcf/d. The total gas produced untill 2012 is 394 BCF and the gas injected is 340 BCF where the maximum average reservoir pressure was recovered and set into a new value of 1881 psi by injection and cushion gas pressure as 1371 psi by withdrawal. If 5th scenario is compared with the others, there is an increase in injection and production performance about 90%.

Reservoir characterization is one of the most important problems in petroleum engineering. It involves forward reservoir modeling that predicts the fluid behavior in the reservoir and inverse problem that calibrates created reservoir models with given data. In this dissertation, we focus on two problems in the field of reservoir characterization: depth of investigation in heterogeneous reservoirs, and history matching and uncertainty quantification of channelized reservoirs. The concept of depth of investigation is fundamental to well test analysis. Much of the current well test analysis relies on analytical solutions based on homogeneous or layered reservoirs. However, such analytic solutions are severely limited for heterogeneous and fractured reservoirs, particularly for unconventional reservoirs with multistage hydraulic fractures. We first generalize the concept to heterogeneous reservoirs and provide an efficient tool to calculate drainage volume using fast marching methods and estimate pressure depletion based on geometric pressure approximation. The applicability of proposed method is illustrated using two applications in unconventional reservoirs including flow regime visualization and stimulated reservoir volume estimation. Due to high permeability contrast and non-Gaussianity of channelized permeability field, it is difficult to history match and quantify uncertainty of channelized reservoirs using traditional approaches. We treat facies boundaries as level set functions and solve the moving boundary problem (history matching) with the level set equation. In addition to level set methods, we also exploit the problem using pixel based approach. The reversible jump Markov Chain Monte Carlo approach is utilized to search the parameter space with flexible dimensions. Both proposed approaches are demonstrated with two and three dimensional examples.

Reservoir management typically focuses on maximizing oil and gas recovery from a reservoir based on facts and information while minimizing capital and operating investments. Modern reservoir management uses history-matched simulation model to predict the range of recovery or to provide the economic assessment of different field development strategies. Geological models are becoming increasingly complex and more detailed with several hundred thousand to million cells, which include large sets of subsurface uncertainties. Current issues associated with history matching, therefore, involve extensive computation (flow simulations) time, preserving geologic realism, and non-uniqueness problem. Many of recent rate optimization methods utilize constrained optimization techniques, often making them inaccessible for field reservoir management. Field-scale rate optimization problems involve highly complex reservoir models, production and facilities constraints and a large number of unknowns. We present a hierarchical multiscale calibration approach using global and local updates in coarse and fine grid. We incorporate a multiscale framework into hierarchical updates: global and local updates. In global update we calibrate large-scale parameters to match global field-level energy (pressure), which is followed by local update where we match well-by-well performances by calibration of local cell properties. The inclusion of multiscale calibration, integrating production data in coarse grid and successively finer grids sequentially, is critical for history matching high-resolution geologic models through significant reduction in simulation time. For rate optimization, we develop a hierarchical analytical method using streamline-assisted flood efficiency maps. The proposed approach avoids use of complex optimization tools; rather we emphasize the visual and the intuitive appeal of streamline method and utilize analytic solutions derived from relationship between streamline time of flight and flow rates. The proposed approach is analytic, easy to implement and well-suited for large-scale field applications. Finally, we present a hierarchical Pareto-based approach to history matching under conflicting information. In this work we focus on multiobjective optimization problem, particularly conflicting multiple objectives during history matching of reservoir performances. We incorporate Pareto-based multiobjective evolutionary algorithm and Grid Connectivity-based Transformation (GCT) to account for history matching with conflicting information. The power and effectiveness of our approaches have been demonstrated using both synthetic and real field cases.

Seismic data have been established as a valuable source of information for the construction of reservoir simulation models, most commonly for determination of the modeled geologic structure, and also for population of static petrophysical properties (e.g. porosity, permeability). More recently, the availability of repeated seismic surveys over the time scale of years (i.e., 4D seismic) has shown promising results for the qualitative determination of changes in fluid phase distributions and pressure required for determination of areas of bypassed oil, swept volumes and pressure maintenance mechanisms. Quantitatively, and currently the state of the art in reservoir model characterization, 4D seismic data have proven distinctively useful for the calibration of geologic spatial variability which ultimately contributes to the improvement of reservoir development and management strategies. Among the limited variety of techniques for the integration of dynamic seismic data into reservoir models, streamline-based techniques have been demonstrated as one of the more efficient approaches as a result of their analytical sensitivity formulations. Although streamline techniques have been used in the past to integrate time-lapse seismic attributes, the applications were limited to the simplified modeling scenarios of two-phase fluid flow and invariant streamline geometry throughout the production schedule. This research builds upon and advances existing approaches to streamline-based seismic data integration for the inclusion of both production and seismic data under varying field conditions. The proposed approach integrates data from reservoirs under active reservoir management and the corresponding simulation models can be constrained using highly detailed or realistic schedules. Fundamentally, a new derivation of seismic sensitivities is proposed that is able to represent a complex reservoir evolution between consecutive seismic surveys. The approach is further extended to manage compositional reservoir simulation with dissolution effects and gravity-convective-driven flows which, in particular, are typical of CO2 transport behavior following injection into deep saline aquifers. As a final component of this research, the benefits of dynamic data integration on the determination of swept and drained volumes by injection and production, respectively, are investigated. Several synthetic and field reservoir modeling scenarios are used for an extensive demonstration of the efficacy and practical feasibility of the proposed developments.

Orientadores: Denis Jose Schiozer, Celio Maschio / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecanica e Instituto de Geociencias / Made available in DSpace on 2018-08-12T23:06:56Z (GMT). No. of bitstreams: 1 MouraFilho_MarcosAntonioBezerrade_M.pdf: 4188788 bytes, checksum: 07988564a5783bc054c31f18ca0a2752 (MD5) Previous issue date: 2006 / Resumo:O processo de ajuste de histórico tradicional normalmente resulta em um único modelo determinístico que é utilizado para representar o reservatório, o que pode não ser suficiente para garantir previsões de produção confiáveis, principalmente para campos em início de produção. Este trabalho apresenta uma análise quantitativa das incertezas dos atributos de reservatório integrada com o processo de ajuste de histórico. Ao invés de ser utilizada uma abordagem determinística, aborda-se uma análise probabilística dos modelos de reservatório resultando em faixas de incerteza de previsão de produção e possibilitando uma melhor visão do comportamento futuro de reservatórios. Na metodologia utilizada neste trabalho, dados de simulação são comparados com dados de produção observados e, de acordo com os afastamentos em relação ao histórico de produção, há uma mudança das probabilidades de ocorrência dos cenários. Em alguns procedimentos propostos, há alterações também nos valores dos atributos incertos, diminuindo sua faixa de incerteza. O maior desafio deste trabalho consiste em determinar uma maneira consistente e confiável para promover a integração da análise de incertezas e ajuste de histórico, aumentando a confiabilidade na previsão de comportamento de reservatórios de petróleo e que seja possível de ser automatizada, facilitando o trabalho e acelerando o processo. Foram testados vários critérios até se alcançar a validação da metodologia proposta. Após a análise dos resultados obtidos, sugere-se uma seqüência de aplicação dos métodos de redução de incerteza propostos na metodologia. A principal contribuição desta metodologia é aumentar a confiabilidade na previsão de comportamento de reservatórios através de simulação numérica e mostrar a necessidade de incorporar incertezas ao processo de ajuste de histórico de produção. Uma outra contribuição deste trabalho é iniciar essa linha de pesquisa propondo e validando alguns métodos para integrar os processos de ajuste e análise de incertezas / Abstract: History matching process usually results in a unique deterministic model that is used torepresent the reservoir, but it may not be enough to guarantee reliable production forecasts, mainly for fields in early production stages. This work presents a quantitative uncertainty analysis of reservoir attributes integrated to the history matching process. Instead of using a deterministic approach, it is used a probabilistic analysis of the reservoir models, resulting in uncertainty ranges for the production forecast and allowing a better prediction of reservoir performance. In the methodology used in this work, simulation data are compared to observed production data and, according to the difference between those data, the probabilities of the scenarios are changed. In some procedures, the probability distribution of the reservoir attributes also change, diminishing their uncertainty range. The main challenges of this work are: (1) the determination of a consistent and reliable procedure to provide the integration of the uncertainty analysis and the history matching process, increasing the reliability in the reservoir performance forecast; and (2) to develop an automatic procedure, making the work easier and speeding up the process. The main contribution of this work is to increase the reliability of production predictions through reservoir simulation models and to show the necessity of incorporating uncertainties in the history matching. Other contribution of this work is start up a research line, proposing and validating some methods to integrate the history matching process and the uncertainty analysis / Mestrado / Ciencias e Engenharia do Petroleo / Mestre em Ciências e Engenharia de Petróleo