Gas coning is the tendency of the gas to drive oil downward in an inverse cone due to the downward movement of gas into the perforations of a producing well thereby reducing oil production and the overall recovery efficiency of the oil reservoir. This work addresses gas coning issues in a naturally fractured reservoir via a numerical simulation approach on a single-well radial cross-section using the ECLIPSE 100 reservoir simulator. Matrix and fracture properties are modelled. Critical rate, breakthrough time and GOR after breakthrough is determined which is used to investigate the effect of matrix and fracture properties on gas coning effective reservoir parameters such as oil flow rate, matrix and fracture porosity, vertical and horizontal matrix and fracture permeability, matrix block size, etc. Results show that reservoir parameters that affect coning include oil flow rate, matrix and fracture porosity, matrix and vertical permeability, anisotropy ratio, perforated interval thickness, density difference and mobility ratio. While matrix block size and fracture spacing have no significant effect on gas coning.

I performed manual History Matching on the E-segment of the Norne field based on available production & pressure data. I used the obtained final match for future prediction. I performed Production Optimization by experimenting with increased and decreased water injection rates.

This research is a simulation study to improve total oil production using ASP flooding method based on simulation model of Norne field C-segment. The black oil model was used for simulations. Remaining oil in the reservoir can be divided into two classes, firstly residual oil to the water flood and secondly oil bypassed by the water flood. Residual oil mainly contains capillary trapped oil. Water flooding only is not able to produce capillary trapped oil so that there is a need for additional technique and force to produce as much as residual oil. One way of recovering this capillary trapped oil is by adding chemicals such as surfactant and alkaline to the injected water. Surfactants are considered for enhanced oil recovery by reduction of oil–water interfacial tension (IFT). The crucial role of alkali in an alkaline surfactant process is to reduce adsorption of surfactant during displacement through the formation. Also alkali is beneficial for reduction of oil-water IFT by in situ generation of soap, which is an anionic surfactant. Generally alkali is injected with surfactant together. On the other hand, polymer is very effective addition by increasing water viscosity which controls water mobility thus improving the sweep efficiency.In the first place, ASP flooding was simulated and studied for one dimensional, two dimensional and three dimensional synthetic models. All these models were built based on C-segment rock properties and reservoir parameters. Based on test runs, well C-3H was selected and used as a main injector in order to execute chemical injection schemes in the C-segment. Five studies such as polymer flooding, surfactant flooding, surfactant-polymer flooding, alkaline-surfactant and alkaline-surfactant-polymer flooding were considered in the injection process and important results from simulator were analyzed and interpreted. Sensitivity analyses were done especially focusing on chemical solution concentration, injection rate and duration of injection time. The polymer flooding project in this study has shown a better outcome compared to water flooding project. Economically best ASP solution flooding case is the flooding with concentration of alkaline at1.5kg/m3, surfactant at 15kg/m3 and polymer at 0.35 kg/m3 injecting for 5 years. AS flooding case for 4 years with alkali concentration at 0.5kg/m3 and surfactant concentration at 25 kg/m3 gave highest NPV value. It was found that surfactant flooding has a promising effect and it is more profitable than polymer flooding for the C segment in terms of NPV. Economic sensitivity analysis (Spider diagram) for low case, base case and high case at different oil prices, chemicals prices, and discount rate were also presented. It was found that change in oil price has significant effect on NPV compared to other parameters while polymer price has the least effect on NPV for high and low cases.

This study presents a detailed analysis of producing gas-oil ratio performance characteristics from conventional reservoir to unconventional reservoir. Numerical simulations of various reservoir fluid systems are included for comparison. In a wide sense of the word, the term of unconventional reservoir is including tight gas sand, coal bed methane, gas hydrate deposits, heavy oil gas shale and etc. In this study we specify the unconventional reservoir to only mean the low and ultra low permeability reservoir, which is including tight or shale reservoir. As an emerging research topic in the E&P industry, shale reservoir’s long-term well performance characteristics are generally not well understood (Anderson et al. 2010). Research methods and techniques for conventional reservoir are usually directly used in this unconventional reservoir analysis. These methods, however, have proven to be too pessimistic (Anderson et al., 2010). Fit-for-purpose approaches or solutions should be introduced in this new topic. Recently, hydraulic fracturing treatment is commonly used in the low matrix permeability reservoir to attain an economic production rate. The difference of well production performance between conventional reservoir and unconventional reservoir is not well known. In this study, we are trying to give a quantitative analysis in order to answer this question.In this study, a “generic” reservoir from field data with constant reserves and size were assumed. This reservoir model is homogeneous and of constant porosity, permeability and initial water saturation. In order to compare the production performance, fluid systems are varied from volatile oil to near critical oil, to gas condensate and to wet gas. The permeability of the reservoir model is also designed from high (conventional reservoir) to ultra low (unconventional), which ranges from 101 to 10-5 mD. Influence from fracture is especially considered because fractures in the low permeability reservoir provide a high conductivity that connects the reservoir matrix to the horizontal well. Fractures in the model are designed with identical geometrical characteristics (length, thickness) and of inner homogeneous properties (porosity, permeability).A black-oil model is used for each reservoir, and its PVT properties are generated with a 31 components EOS model using Whitson-Torp procedure (Whitson et al., 1983). Reservoir fluid systems equilibrium calculation in the black-oil model is done using the initial gas-oil ratio. We have compared the well’s production performance for each fluid system.Based on the industry experience, two standards are used in reservoir simulation control: gas production rate and cumulative revenue. The gas production rate with 10 ×106 ft3/day in the first 10 days or the cumulative revenue equal to 5 ×105 USD from the first 10 days is set as the standard for the commercial well rate. All of these simulations are run under the control of these two types which have just been mentioned. A case of liquid rich gas reservoir is analyzed systematically, to compare its production performance when reservoir permeability is changed from high to low. We are interested in how much oil or gas condensate can be extracted from the “reservoir” if same initial fluids in the reservoir but of a different permeability. This study is useful and practical, particularly for the industry in the era of “high” oil price and “low” gas price in North America.The simulation results show that we can extract more liquid from the reservoir if the matrix permeability is higher, particularly for the reservoir with initially large oil contents (volatile oil reservoir, near critical reservoir and gas condensate reservoir). Fracturing treatment in unconventional reservoir is required to attain an economic production rate. We also realize that for the required number of fractures and reservoir’s matrix permeability, there exists linear correlation in log-log plot in the low-permeability reservoir. In this study, the unique optimization software Pipe-It and reservoir simulator SENSOR are used. Optimal simulation results of permeability combination are obtained by the module Optimizer in Pipe-It.

In this study, based on the work of Vogel, we generated the Inflow Performance Relationship (IPR) curves and its dimensionless form at any stage of depletion using black-oil simulator results. The IPR was generated for horizontal well with gas and water coning problems, producing from thin oil reservoir sandwiched between gas cap and aquifer. Two empirical IPR equations adopted from SPE paper by Whitson was also presented here. The first empirical relationship was developed based on simulated data for each reservoir pressure (stage of depletion) while the second relationship was developed based on all generated data.A fully implicit black-oil Cartesian model with total grid number of 1480 and 150 ft total thickness was used as reservoir model. The horizontal well extends through the full length of reservoir in y-direction with only one grid number along the horizontal section which makes the model a 2D problem. Sensor reservoir simulator and Pipe-It software were utilized to generate the IPR data.This work also includes a sensitivity study to understand the effect of several parameters to gas and water coning behavior, well placement optimization, coning collapse study, and the effect of coning to maximum well production rate. In coning collapse study, a relationship between flowing bottom-hole pressure and reservoir pressure when the cone collapse is provided in graphical form. This could be useful in field application where chocking the well to lower flowing bottom-hole pressure has become one alternative to reduce coning problems.

Water coning is a complex phenomenon that depends on a large number of variables which include among others: production rate, perforation interval, mobility ratio, capillary pressure, etc. Its production can greatly affect the productivity of a well and the reservoir at large. In fractured reservoirs, the phenomenon is more complex owing to the high permeability of the fractures in the porous media. With this complexity in mind, water coning behaviour in fractured reservoir was studied by simulating a reservoir supported by a strong aquifer using ECLIPSE-100 Black-Oil Simulator. The water cut (WCT), oil production rate (OPR) and water saturation (BWSAT) at the producing interval (Block 1, 1, 7) were used to evaluate the coning phenomenon in a fractured reservoir. In the course of the study, sensitivity analyses on the modelled reservoir’s anisotropy ratio (kv/kh), production rate (q), storativity capacity (ω), fracture width (b) and fracture permeability (kf) were conducted to evaluate their effect on coning behaviour in fractured reservoir. The results obtained depict that while the anisotropy ratio is very significant in water cut and water saturation at the perforating interval it has no adverse effect on oil production rate. It was however, observed that the water cut and oil production rate decreased as the production rate (q) increased. Furthermore, the water cut, oil production rate and water saturation (BWSAT) from the fractured reservoir is sensitive to the storativity capacity (ω) depending on the fracture porosity (φf). Conversely, the fracture’s width (b) and permeability (kf) have no significant effect on the coning behaviour of the modelled fracture reservoir. However, anisotropy ratio (kv/kh), production rate as well as storativity capacity (ω) are significant parameters in evaluating coning phenomenon in fractured reservoirs.

Thesis (Ph. D.)--University of Texas at Austin, 1999. / Vita. Includes bibliographical references (leaves 237-240). Available also in a digital version from Dissertation Abstracts.

Thesis (Ph. D.)--University of Texas at Austin, 1999. / Vita. Includes bibliographical references (leaves 254-259). Available also in a digital version from Dissertation Abstracts.

Thesis (Ph. D.)--University of Texas at Austin, 2000. / Vita. Includes bibliographical references (leaves 152-158). Available also in a digital version from Dissertation Abstracts.

Thesis (Ph. D.)--University of Texas at Austin, 2001. / Vita. Includes bibliographical references. Available also from UMI/Dissertation Abstracts International.