Browsing by Subject "Water flooding"
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Item Application of real options to valuation and decision making in the petroleum E&P industry(2010-12) Xu, Liying, 1962-; Van Rensburg, W. C. J.; Sepehrnoori, Kamy, 1951-This study is to establish a binomial lattice method to apply real options theory to valuation and decision making in the petroleum exploration and production industry with a specific focus on the switching time from primary to water flooding oil recovery. First, West Texas Intermediate (WTI) historical oil price evolution in the past 25 years is studied and modeled with the geometric Brownian motion (GBM) and one-factor mean reversion price models to capture the oil price uncertainty. Second, to conduct real options evaluation, specific reservoir simulations are designed and oil production profile for primary and water flooding oil recovery for a synthetic onshore oil reservoir is generated using UTCHEM reservoir simulator. Third, a cash flow model from producing the oil reservoir is created with a concessionary fiscal system. Finally, the binomial lattice real options evaluation method is established to value the project with flexibility in the switching time from primary to water flooding oil recovery under uncertain oil prices. The research reaches seven conclusions: 1) for the GBM price model, the assumptions of constant drift rate and constant volatility do not hold for WTI historical oil price; 2) one-factor mean reversion price model is a better model to fit the historical WTI oil prices than the GBM model; 3) the evolution of historical WTI oil prices from January 2, 1986 to May 28, 2010 was according to three price regimes with different long run prices; 4) the established real options evaluation method can be used to identify the best time to switch from primary to water flooding oil recovery using stochastic oil prices; 5) with the mean reversion oil price model and the most updated cost data, the real options evaluation method finds that the water flooding switching time is earlier than the traditional net present value (NPV) optimizing method; 6) the real options evaluation results reveals that most of time water flooding should start when oil price is high, and should not start when oil price is low; and 7) water flooding switching time is sensitive to oil price model to be used and to the investment and operating costs.Item Capacitance resistance modeling for improved characterization in waterflooding and thermal recovery projects(2016-12) Duribe, Victor Chijioke; Edgar, Thomas F.; Lake, Larry W.; Sanchez, Isaac C; Baldea, Michael; Lasdon, Leon SRates are typically one of the most measured in an oil recovery project. The abundance of these types of data is explained partly by their relative ease of collection. Additionally, their collection and reporting is often required for logistical as well as financial purposes. Numerous researchers have shown the potency of using these data for characterization and management of oil reservoirs under primary or secondary recovery. Reduced-order models typically use these measurements as input to characterize reservoirs. The capacitance resistance model (CRM) is one such reduced order modeling method. This model uses well rates (and bottomhole pressure data, if available) to characterize a reservoir in a cheap and fast way. In characterizing an oil reservoir, the CRM and its linear counterpart (the Integrated Capacitance Resistance Model or ICRM) use historical data available at the wells to infer connectivity and flow paths between these wells through a set of model parameters. This use of readily available data, enabled by the speed of these models, creates a powerful tool that can be used as an alternative or as a complement to more expensive and time consuming traditional reservoir management tools. The CRM was initially developed for secondary recovery (i.e., water-flooding) but has been shown to work very well for primary recovery and many enhanced oil recovery (EOR) processes. The increasing industry acceptance of this modeling method is because of the work researchers who have contributed in expanding the capabilities of this modeling approach. However, key questions such as the impact of noise of CRM and ICRM performance remain. Additionally, a rigorous way of designing injection rates (a key input into the CRM model) such that parameter estimation is optimal has not been addressed. Finally, ideas about the applicability of the CRM modeling method to thermal EOR processes has not been explored. This research aims to address these questions. By addressing these questions, this work aims to contribute towards deepening current under-standing of the CRM modeling method and to opening new avenues for its application and research.Item Efficiency of low salinity polymer flooding in sandstone cores(2012-05) Kozaki, Chie; Pope, Gary A.; Mohanty, Kishore KumarWaterflooding has been used for many decades as a way of recovering oil from petroleum reservoirs. Historically the salinity of the injection water has not been regarded as a key variable in determining the amount of oil recovered. In recent years, however, evidence of increased oil recovery by injection of low salinity water has been observed in laboratories and fields. The technique is getting wider attention in the oil industry because it is more cost-effective than other EOR techniques. The present work demonstrates the synergy of low salinity water flooding and polymer flooding in the laboratory scale. The use of low salinity polymer solution in polymer flooding has significant benefits because considerably lower amount of polymer is required to make the solution of a target viscosity. Low salinity polymer flooding can also increase oil recovery by lowering residual oil saturation and achieve faster oil recovery by improving sweep efficiency. Several coreflood experiments were conducted to study the efficiency of low salinity water flooding and low salinity polymer flooding in mixed-wet Berea sandstone cores. All the core samples were aged with a crude oil at 90oC for 30-60 days before the tests. All the polymer floods were conducted in the tertiary mode. A synthetic formation brine (33,800 ppm) was chosen for high salinity water and a NaCl brine (1,000 ppm) for low salinity water. Medium molecular weight HPAM polymer, FlopaamTM 3330S was used due to the low/moderate permeability of the Berea sandstone cores used in this study. Coreflood tests indicate that injection of low salinity polymer solution reduces residual oil saturation by 5-10% over that of the high salinity waterflood. A part of the residual saturation reduction is due to low salinity and this reduction is achieved in less pore volumes of injection in the presence of polymers. Effluent ion analysis from both low salinity water flooding and low salinity polymer flooding showed a slight increase in divalent cation concentrations after the polymer breakthrough. Cation bridging may play a role in oil wettability and low salinity injection desorbs some of these cations.Item Evaluation of EOR Potential by Gas and Water Flooding in Shale Oil Reservoirs(2013-05) Chen, Ke; Sheng, James; Menouar, Habib K.; Heinze, Lloyd R.The demand for oil and natural gas will continue to increase for the foreseeable future; unconventional resources such as tight oil, shale gas, shale oil will pose an irreplaceable role in oil and gas industry to fill the gap between demand and supply. With the relatively modest natural gas price, producing oil from unconventional shale reservoirs, which are less common and less well understood than conventional sandstone and carbonate reservoirs, has attracted more and more interest from oil operators. Through many tremendous efforts on the development of shale resources, the horizontal well-drilling with multiple transverse fractures has proven to be an effective method for shale gas reservoirs exploitation and it has also been used in extracting oil from shale reservoirs by some operators. However, the oil recovery is very low (5-10%). For the important role of shale resources in future oil and gas industry, more stimulation and production strategies must be considered and tested to find better methods to improve oil production from shale reservoirs. Gas flooding and water flooding, relatively simple and cheaper EOR techniques, which have been successfully implemented in conventional and some unconventional tight oil reservoirs for a long time, are considered in our work. A black-oil simulator developed by Computer Modeling Group Ltd was selected in our work. We build a reservoir model of 200ft long, 1000ft wide and 200 ft thick two 1-ft wide ×1000-ft long hydraulic fractures to simulate gas flooding and water flooding in shale oil reservoirs. We first validate a base model, and discussed the determination of miscibility parameter and injection pressure. Production behavior and oil recovery of different plans are discussed through sensitivity studies. Simulation results of primary production, gas injection and water injection are compared in this thesis. Results show that miscible gas injection has better effect on improving oil recovery from shale reservoirs than water injection. Solvent injected into the reservoirs above MMP can be fully miscible with oil, reducing oil viscosity greatly, and can lead a better sweep efficiency besides pressure maintenance. Our simulation results indicate that the oil recovery can be increased up to 15.1% by using gas injection in a hydraulically fractured shale reservoir, compared with the original 6.5% recovery from the primary depletion. This thesis provides a preliminary analysis to regarding the EOR potentials by gas and water flooding in shale oil reservoirs. The results show that miscible gas flooding could be a good prospect in future development of shale oil resources.Item Experimental investigation of the effect of increasing the temperature on ASP flooding(2011-12) Walker, Dustin Luke; Pope, Gary A.; Weerasooriya, UpaliChemical EOR processes such as polymer flooding and surfactant polymer flooding must be designed and implemented in an economically attractive manner to be perceived as viable oil recovery options. The primary expenses associated with these processes are chemical costs which are predominantly controlled by the crude oil properties of a reservoir. Crude oil viscosity dictates polymer concentration requirements for mobility control and can also negatively affect the rheological properties of a microemulsion when surfactant polymer flooding. High microemulsion viscosity can be reduced with the introduction of an alcohol co-solvent into the surfactant formulation, but this increases the cost of the formulation. Experimental research done as part of this study combined the process of hot water injection with ASP flooding as a solution to reduce both crude oil viscosity and microemulsion viscosity. The results of this investigation revealed that when action was taken to reduce microemulsion viscosity, residual oil recoveries were greater than 90%. Hot water flooding lowered required polymer concentrations by reducing oil viscosity and lowered microemulsion viscosity without co-solvent. Laboratory testing of viscous microemulsions in core floods proved to compromise surfactant performance and oil recovery by causing high surfactant retention, high pressure gradients that would be unsustainable in the field, high required polymer concentrations to maintain favorable mobility during chemical flooding, reduced sweep efficiency and stagnation of microemulsions due to high viscosity from flowing at low shear rates. Rough scale-up chemical cost estimations were performed using core flood performance data. Without reducing microemulsion viscosity, field chemical costs were as high as 26.15 dollars per incremental barrel of oil. The introduction of co-solvent reduced chemical costs to as low as 22.01 dollars per incremental barrel of oil. This reduction in cost is the combined result of increasing residual oil recovery and the added cost of an alcohol co-solvent. Heating the reservoir by hot water flooding resulted in combined chemical and heating costs of 13.94 dollars per incremental barrel of oil. The significant drop in cost when using hot water is due to increased residual oil recovery, reduction in polymer concentrations from reduced oil viscosity and reduction of microemulsion viscosity at a fraction of the cost of co-solvent.Item The use of capacitance-resistance models to optimize injection allocation and well location in water floods(2009-08) Weber, Daniel Brent; Edgar, Thomas F.; Lake, Larry W.Reservoir management strategies traditionally attempt to combine and balance complex geophysical, petrophysical, thermodynamic and economic factors to determine an optimal method to recover hydrocarbons from a given reservoir. Reservoir simulators have traditionally been too large and run times too long to allow for rigorous solution in conjunction with an optimization algorithm. It has also proven very difficult to marry an optimizer with the large set of nonlinear partial differential equations required for accurate reservoir simulation. A simple capacitance-resistance model (CRM) that characterizes the connectivity between injection and production wells can determine an injection scheme maximizes the value of the reservoir asset. Model parameters are identified using linear and nonlinear regression. The model is then used together with a nonlinear optimization algorithm to compute a set of future injection rates which maximize discounted net profit. This research demonstrates that this simple dynamic model provides an excellent match to historic data. Based on three case studies examining actual reservoirs, the optimal injection schemes based on the capacitance-resistive model yield a predicted increase in hydrocarbon recovery of up to 60% over the extrapolated exponential historic decline. An advantage of using a simple model is its ability to describe large reservoirs in a straightforward way with computation times that are short to moderate. However, applying the CRM to large reservoirs with many wells presents several new challenges. Reservoirs with hundreds of wells have longer production histories – new wells are created, wells are shut in for varying periods of time and production wells are converted to injection wells. Additionally, ensuring that the production data to which the CRM is fit are free from contamination or corruption is important. Several modeling techniques and heuristics are presented that provide a simple, accurate reservoir model that can be used to optimize the value of the reservoir over future time periods. In addition to optimizing reservoir performance by allocating injection, this research presents a few methods that use the CRM to find optimal well locations for new injectors. These algorithms are still in their infancy and represent the best ideas for future research.