The world needs energy – and over the short and medium term it is clear that much of our global energy consumption will come from fossil sources such as oil, gas and coal. With the current growing demand for oil led by major energy consuming countries such as China and India, securing new oil resources is a critical challenge for the oil industry. Each year, new production is needed to compensate the natural decline of existing wells, and the additional production required to satisfy the yearly demand for hydrocarbon energy that will represent approximately 9% of the worldwide total production. For this growth to be sustainable, a strong focus will have to be placed on finding new discoveries and/or optimizing oil production from current resources. The cost associated with the first option is significant. Therefore, reservoir management teams all over the world will have to cater for this demand mainly by maximizing hydrocarbon recovery factors through Enhanced Oil Recovery (EOR) processes. EOR consists of methods aimed at increasing ultimate oil recovery by injecting appropriate agents not normally present in the reservoir, such as chemicals, solvents, oxidizers and heat carriers in order to induce new mechanisms for displacing oil. Chemical flooding is one of the most promising and broadly applied EOR processes which have enjoyed significant research and pilot testing during the 1980s with a significant revival in recent years. However, its commercial implementation has been facing several technical, operational and economic challenges. Chemical flooding is further subdivided into polymer flooding, surfactant flooding, alkaline flooding, miscellar flooding, alkaline-surfactant-polymer (ASP) flooding. ASP flooding is a form of chemical enhanced oil recovery (EOR) that can allow operators to extend reservoir pool life and extract incremental reserves currently inaccessible by conventional EOR techniques such as waterflooding. Three chemical inject in the ASP process which is synergistic. In the ASP process, Surfactants are chemicals that used to reduce the interfacial tension between the involved fluids, making the immobile oil mobile. Alkali reduces adsorption of the surfactant on the rock surfaces and reacts with acids in the oil to create natural surfactant. Polymer improves the sweep efficiency. By simulating ASP flooding for several cases, with different chemical concentrations, injection length, time of injection, current well optimization and new well placement, this report suggests a number of good alternatives. Simulations showed that the most effective method was not the most profitable. From the simulation results and economic analysis, ASP flooding can be a good alternative for the Norne E-segment. But the margins are not significant, so fixed costs (such as equipment rental) will be of crucial importance.

In petroleum fields, the essence of well placement is to develop and maintain petroleum reservoirs in order to achieve maximum production for economic benefit. Maximum production can be achieved with more oil wells, but few optimal numbers of wells in good location reduces economic costs and increase recovery. The best location for the placement of oil, gas or water wells depends on reservoir and fluid properties, well and surface equipment specifications, as well as economic parameters [1].The objective of the study is to determine the net present value from few well placements in the Norne C-segment reservoir by either obtaining the same or more oil production/recovery compared to the base case wells. New well placement in a reservoir simulation model uses an industrial standard ECLIPSE reservoir simulator. Manually simulation approach is used to locate high oil saturation grids for the new well placement. From the base case simulation result, a total number of thirteen wells were discovered, nine producers and four injectors. The production and injection wells were classified with a suffix according to the production templates B, D, K and injection template C respectively.The base case wells removed and new well placed from exhaustive simulation runs for two different scenario cases. A total number of ten wells, six producers and four injectors were placed in each scenario. In order to obtain maximum oil recovery, the producers are placed horizontally while injectors remain the same as those from the base case. The new well placements in the scenario cases are identified with the suffix “P-H” for producers and “I-H” for injectors. Simulation results, the total oil produced for wells in each field case from the start year 1997 to December 2015, (end of production) can be seen in Table 10, 11 and 12 in chapter 6. The cumulative oil produced from each field case is the same as the total oil produced from all the wells in each case. The cumulative field oil and gas production from the start of production, November 1997 to December 2015 is 41.3 million Sm3 oil and 260 million Sm3 of gas for base case, 42.8 million Sm3 oil and 269 million Sm3 of gas for scenario 1 case, 43.2 million Sm3 oil and 272 million Sm3 of gas for scenario 2 case. The recovery factor for base case is 28%, scenario 1 & 2 are 29.0% and 29.3%. Each field case uses drive mechanisms, gas injection and water injection to support oil production and maintain pressure in the each field case. The total gas and water injected in the base case field were 9.6 billion Sm3 and 78.8 million Sm3 respectively. In scenario 1, a total of 8.6 billion Sm3 of gas and 81.6 million Sm3 of water was injected and in Scenario 2, 8.6 billion Sm3 of gas and 81.3 million Sm3 of water was injected. The Net present values for the three cases were calculated taking into account the economic costs such as well cost, cost of gas and water injection. Sensitization was done on the oil price ($25, $35 and $45). The NPV results from Table 19 prove that all case projects are acceptable, but scenario 2 is the most economical as it has the highest NPV of $4,026 million based on $35-medium oil price that was considered.

Thesis (M.Sc.)--University of Alberta, 2010. / Title from PDF file main screen (viewed on Apr. 1, 2010). A thesis submitted to the Faculty of Graduate Studies and Research in partial fulfillment of the requirements for the degree of Master of Science in Petroleum Engineering, Department of Civil and Environmental Engineering, University of Alberta. Includes bibliographical references.

Thesis (M.S.)--West Virginia University, 2004. / Title from document title page. Document formatted into pages; contains ix, 80 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 33-34).

Thesis (Ph. D.)--University of Texas at Austin, 1998. / Vita. Includes bibliographical references (leaves 276-281). Available also in a digital version from Dissertation Abstracts.

Thesis (Ph. D.)--University of Texas at Austin, 2005. / Supervisor: Russell T. Johns. Vita. Includes bibliographical references.

<p> The objective of this study is threefold: 1) Build a dual-porosity, geological reservoir model of Niobrara formation in the Wishbone Section of the DJ Basin. 2) Use the geologic static model to construct a compositional model to assess performance of Well 1N in the Wishbone Section. 3) Compare the modeling results of this study with the result from an eleven-well modeling study (Ning, 2017) of the same formation which included the same well. The geologic model is based on discrete fracture network (DFN) model (Grechishnikova 2017) from an outcrop study of Niobrara formation.</p><p> This study is part of a broader program sponsored by Anadarko and conducted by the Reservoir Characterization Project (RCP) at Colorado School of Mines. The study area is the Wishbone Section (one square mile area), which has eleven horizontal producing wells with initial production dating back to September 2013. The project also includes a nine-component time-lapse seismic. The Wishbone section is a low-permeability faulted reservoir containing liquid-rich light hydrocarbons in the Niobrara chalk and Codell sandstone.</p><p> The geologic framework was built by Grechishnikova (2017) using seismic, microseismic, petrophysical suite, core and outcrop. I used Grechishnikova&rsquo;s geologic framework and available petrophysical and core data to construct a 3D reservoir model. The 3D geologic model was used in the hydraulic fracture modeling software, GOHFER, to create a hydraulic fracture interpretation for the reservoir simulator and compared to the interpretation built by Alfataierge (2017). The reservoir numerical simulator incorporated PVT from a well within the section to create the compositional dual-porosity model in CMG with seven lumped components instead of the thirty-two individual components. History matching was completed for the numerical simulation, and rate transient analysis between field and actual production are compared; the results were similar. The history matching parameters are further compared to the input parameters, and Ning&rsquo;s (2017) history matching parameters.</p><p> The study evaluated how fracture porosity and rock compaction impacts production. The fracture porosity is a major contributor to well production and the gas oil ratio. The fracture porosity is a major sink for gathering the matrix flow contribution. The compaction numerical simulations show oil production increases with compaction because of the increased compaction drive. As rock compaction increases, permeability and porosity decreases. How the numerical model software, CMG, builds the hydraulic fracture, artificially increases the original oil-in-place and decreases the recovery factor. Furthermore, grid structure impacts run-time and accuracy to the model. Finally, outcrop adds value to the subsurface model with careful qualitative sedimentology and structural extrapolations to the subsurface by providing understanding between the wellbore and seismic data scales.</p><p>

Orientador: Denis José Schiozer / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica e Instituto de Geociências / Made available in DSpace on 2018-08-20T19:01:11Z (GMT). No. of bitstreams: 1 Cotrim_HenriqueAraujo_M.pdf: 2298003 bytes, checksum: 2551e58ec65d13716630850ca27cd695 (MD5) Previous issue date: 2012 / Resumo: No contexto da engenharia de reservatórios de petróleo, é bem conhecida a importância do trabalho de seleção de estratégias de produção. No caso específico em que há restrição de tratamento de fluidos na superfície, a alocação de vazões de produção e injeção dos poços é mais um item a ser otimizado. Quando o problema envolve diversas unidades segregadas de reservatórios, cada qual caracterizado por seu próprio modelo de fluxo, as simulações não devem ser consideradas isoladamente, pois elas estão efetivamente acopladas pelos limites das vazões totais de produção e/ou injeção. Neste cenário de múltiplos reservatórios, o presente trabalho propõe o estudo de alocação das vazões de produção utilizando abordagens tradicionais e também aplicando a Modelagem Integrada de Produção (MIP) simplificada considerando uma estratégia de produção fixa. A MIP simplificada consiste no uso de um aplicativo que gerencia o acoplamento explícito entre simulações de reservatórios e sistemas de produção, sendo este último elemento representado de forma simplificada. Neste trabalho, foi selecionado o limite de escoamento de gás como restrição operacional de superfície em dois casos de estudo e aplicados os procedimentos tradicionais de simulação segregada com rateio manual das vazões e união dos modelos para simulação de uma malha única, além da MIP simplificada. Em cada abordagem, foram aplicados três métodos de alocação de vazões disponíveis no simulador comercial adotado e implementados em rotina específica (RAV). Os resultados obtidos mostram que o uso de diferentes algoritmos de alocação de vazões pode levar a alterações na previsão de VPL superiores a 12% e indicam que a MIP simplificada é válida e pode ser considerada a melhor alternativa em cenários específicos, quando a otimização manual do rateio e a união das malhas não se apresentarem como soluções simples / Abstract: The selection of production strategies for petroleum field development is an important task. The specific case in which there are constrained surface facilities, the allocation of production and injection well rates is one more item to be optimized. When the problem involves several segregated reservoir units, each of which characterized by its own geological model, the simulations should not be considered as isolated because they are effectively coupled by the limits of the total flow of production and injection. In this scenario of multiple reservoirs, this work proposes the study of production rates allocation using traditional approaches and also applying the simplified Integrated Production Modeling (IPM), considering a fixed position for the wells. The simplified IPM consists of using an application that manages an explicit coupling between reservoir simulators and production systems, the latter element represented in a simplified form. In this work, the total gas rate was selected as the surface constraint in two case studies. The traditional procedures of segregated simulation with manual optimization and amalgamating the simulation models into a single model are used, besides the simplified IPM. In each approach, three methods are applied for well rates allocation, available in the adopted commercial simulator and implemented in the specific routine (RAV). The obtained results show that the use of different flow allocation algorithms can lead to changes in estimated NPV above 12% and indicate that the simplified IPM is valid and it can be considered the best alternative in some specific scenarios / Mestrado / Reservatórios e Gestão / Mestre em Ciências e Engenharia de Petróleo

<p> In this study, imbibition experiments are used to explain the significant fluid loss, often more than 70%, of injected water during well stimulation and flowback in the context of natural gas production from shale formations. Samples from a 180 ft. long section of a vertical well were studied via spontaneous and forced imbibition experiments, at lab-scale, on small samples with characteristic dimensions of a few cm; in order to quantify the water imbibed by the complex multi-porosity shale system. The imbibition process is, typically, characterized by a distinct transition from an initial linear rate (vs. square root of time) to a much slower imbibition rate at later times. These observations along with contact angle measurements provide an insight into the wettability characteristics of the shale surface. Using these observations, together with an assumed geometry of the fracture system, has made it possible to estimate the distance travelled by the injected water into the formation at field scale. </p><p> Shale characterization experiments including permeability measurements, total organic carbon (TOC) analysis, pore size distribution (PSD) and contact angle measurements were also performed and were combined with XRD measurements in order to better understand the mass transfer properties of shale. The experimental permeabilities measured in the direction along the bedding plane (10^&ndash;1&ndash;10^&ndash;2 mD) and in the vertical direction (~10^&ndash;4 mD) are orders of magnitude higher than the matrix permeabilities of these shale sample (10^&ndash;5 to 10^&ndash;8 mD). This implies that the fastest flow in a formation is likely to occur in the horizontal direction, and indicates that the flow of fluids through the formation occurs predominantly through the fracture and micro-fracture network, and hence that these are the main conduits for gas recovery. The permeability differences among samples from various depths can be attributed to different organic matter content and mineralogical characteristics, likely attributed to varying depositional environments. The study of these properties can help ascertain the ideal depth for well placement and perforation. </p><p> Forced imbibition experiments have been carried out to better understand the phenomena that take place during well stimulation under realistic reservoir conditions. Imbibition experiments have been performed with real and simulated frac fluids, including deionized (DI) water, to establish a baseline, in order to study the impact on imbibition rates resulting from the presence of ions/additives in the imbibing fluid. Ion interactions with shales are studied using ion chromatography (IC) to ascertain their effect on imbibition induced porosity and permeability change of the samples. It has been found that divalent cations such as calcium and anions such as sulfates (for concentrations in excess of 600 ppm) can significantly reduce the permeability of the samples. It is concluded, therefore, that their presence in stimulating fluids can affect the capillarity and fluid flow after stimulation. We have also studied the impact of using fluoro-surfactant additives during spontaneous and forced imbibition experiments. A number of these additives have been shown to increase the measured contact angles of the shale samples and the fluid recovery from them, thus making them an ideal candidate for additives to use. Their interactions with the shale are further characterized using the Dynamic Light Scattering (DLS) technique in order to measure their hydrodynamic radius to compare it with the pore size of the shale sample.</p><p>

<p> To efficiently produce oil from unconventional reservoirs, it is imperative to determine and understand the geomechanical properties of the formation. But, due to the high cost of obtaining these properties from geomechanical well logs, businesses are looking for all possible ways to cut cost. The plummeting oil prices have been reflected in company spending and have driven companies to prioritize focusing attention on the rising production costs and venture all possible ways to reduce these costs. The real challenge is how to preserve these profitable gains? There is a need for an alternate and cost- effective way to obtain geomechanical properties of the rocks. </p><p> By utilizing Data Analytics, Data Mining, and ANN, patterns are observed between parameters from large amounts of data and, thus, important information regarding the formation can be understood. In this study, a relationship between conventional well logs and geomechanical well logs are established. Properties such as Young&rsquo;s Modulus, Poisson&rsquo;s Ratio, Shear Modulus, Bulk Modulus, and Minimum Horizontal Stress are determined from Conventional Logs such as Gamma Ray and Density Log utilizing ANN. Ultimately, data-driven models are developed to predict accurate geomechanical properties for future wells of the Upper and Middle Bakken Formation. Finally, the efficacy of the data-driven models achieved is tested on randomly selected new wells that were not used in the training of the model. The accurate prediction and analysis of these properties help in better reservoir characterization and efficient production from the future wells in the Bakken Formation.</p><p>