Browsing by Subject "Reservoir modeling"
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Item Assessing reservoir performance and modeling risk using real options(2012-05) Singh, Harpreet; Srinivasan, Sanjay; Lake, Larry W.Reservoir economic performance is based upon future cash flows which can be generated from a reservoir. Future cash flows are a function of hydrocarbon volumetric flow rates which a reservoir can produce, and the market conditions. Both of these functions of future cash flows are associated with uncertainties. There is uncertainty associated in estimates of future hydrocarbon flow rates due to uncertainty in geological model, limited availability and type of data, and the complexities involved in the reservoir modeling process. The second source of uncertainty associated with future cash flows come from changing oil prices, rate of return etc., which are all functions of market dynamics. Robust integration of these two sources of uncertainty, i.e. future hydrocarbon flow rates and market dynamics, in a model to predict cash flows from a reservoir is an essential part of risk assessment, but a difficult task. Current practices to assess a reservoir’s economic performance by using Deterministic Cash Flow (DCF) methods have been unsuccessful in their predictions because of lack in parametric capability to robustly and completely incorporate these both types of uncertainties. This thesis presents a procedure which accounts for uncertainty in hydrocarbon production forecasts due to incomplete geologic information, and a novel real options methodology to assess the project economics for upstream petroleum industry. The modeling approach entails determining future hydrocarbon production rates due to incomplete geologic information with and without secondary information. The price of hydrocarbons is modeled separately, and the costs to produce them are determined based on market dynamics. A real options methodology is used to assess the effective cash flows from the reservoir, and hence, to determine the project economics. This methodology associates realistic probabilities, which are quantified using the method’s parameters, with benefits and costs. The results from this methodology are compared against the results from DCF methodology to examine if the real options methodology can identify some hidden potential of a reservoir’s performance which DCF might not be able to uncover. This methodology is then applied to various case studies and strategies for planning and decision making.Item Capacitance resistance modeling for primary recovery, waterflood and water-CO₂ flood(2012-08) Nguyen, Anh Phuong; Edgar, Thomas F.; Lake, Larry W.; Lasdon, Leon S.; Bonnecaze, Roger T.; Sharma, Mukul M.Reservoir characterization is very important in reservoir management to plan, monitor, predict and optimize oil production. Reservoir simulation is well-accepted in reservoir management but it requires many inputs, needs months to set up and complete a set of simulation runs, and contains large uncertainty in physical and geological properties. Therefore, simpler methods that provide quick results to complement or substitute reservoir simulation are important in decision making. Capacitance resistance model (CRM) is one of the methods. CRM is an input-output model derived from a continuity equation to quantify producer-injector connection strength during waterflood using solely production data. This work improves the CRM application method for waterflood and develops CRM theories and application methods for other recovery periods such as primary recovery and water-CO2 flood. A West Texas field test was carried out to validate CRM for a waterflood. The CRM fit was evaluated and used to optimize the oil production by changing injection rates. Through this first field experiment, a CRM application procedure was developed. With the CRM optimized injection schedule, the field gained 5372 bbls of additional oil production increase after one year. This research also quantitatively validates the CRM gain and time constant using synthetic fields and compares them to parameters of the streamline model, a complex model with similar purposes to the CRM. The CRM provides similar results as the streamline model with fewer inputs. The CRM was extended to primary recovery and water-CO2 flood. A new CRM equation – the integrated CRM (ICRM) - for primary recovery was developed and validated on many synthetic fields and an Oman field. The model can estimate dynamic pore volume, productivity index and average reservoir pressure that compare closely to simulated values and field knowledge. Additionally, the ability of CRM to quantify injector-producer connection strength and predict fluid production was examined on a synthetic water-CO2 flood field. A new oil production model to be used with CRM application in water-CO2 flood was developed and validated on synthetic data. The model predicts oil production from injection rate and relative permeability. CRM has successfully optimized waterflood on a West Texas field by reallocating the water from ineffective to effective injectors. New interpretations of the CRM parameters enable quantitative validation and integration of the CRM results with other methods. In primary recovery, the ICRM can estimate reservoir properties without requiring well testing which can cause loss of production. The CRM and the new oil production model can quickly characterize water-CO2 flood for short term production monitoring.Item Characterizing the petrophysical properties of shallow marine environments and their potential as methane hydrate reservoirs(2015-05) Nole, Michael Anthony; Daigle, Hugh; Mohanty, KishoreIn shallow marine sedimentary environments, characterization of sediment petrophysical and thermodynamic properties is imperative for understanding the subsurface transport of fluids and their chemical constituents. This work first presents an objective method of scanning electron microscope image analysis that directly quantifies microporosity in clay-rich, fine-grained sediments typical of the shallow marine subsurface. The method is powerful because it is fast, easy, and provides a direct microporosity estimation technique to augment or replace experimental data. When used appropriately, the method can be implemented on microporous sediments and sedimentary rock in general. With an understanding of how microporosity manifests in shallow marine sediments, the impact of small pore sizes on methane hydrate solubility is then examined for core samples taken from 3 sites in the Nankai Trough offshore Japan, an area that has been heavily surveyed in recent years for its potential to host economically recoverable deposits of methane hydrate for use as a natural gas resource. Small pores in fine-grained shaley intervals are shown to significantly increase the aqueous solubility of methane in pore water relative to surrounding coarser-grained sediment strata, which can have broad implications for methane hydrate formation, including lack of formation in the clayey intervals and strong diffusive fluxes of methane into coarser sediment layers. Finally, an existing methane hydrate reservoir simulator is modified to model methane hydrate accumulations in marine environments with heterogeneous layered sediments. The impact of pore size on solubility is included in the model along with steady state microbial methanogenesis and diffusion of salt in the pore water. The simulator is then used to successfully model methane hydrate accumulations in 1D and 2D at Walker Ridge Site 313 in the Gulf of Mexico, where well logs and seismic surveys throughout the region abound. This work is an important step in building a general 3D methane hydrate reservoir simulator for shallow marine environments around the globe.Item Modeling of point bar geology using a grid transformation scheme and geostatistics(2015-12) Li, Henry; Sepehrnoori, Kamy, 1951-; Srinivasan, SanjayPoint bars, the convex inner banks of meandering rivers, exhibit distinct heterogeneities. Modeling these heterogeneities is essential because of the presence of mud/silt layers in point bars impede the flow of fluids in processes strongly controlled by buoyancy or gravity such as the steam chamber rise during Steam-Assisted Gravity Drainage (SAGD). This thesis details the modeling of point bars using geological trends and well data to supplement geostatistical simulation. The modeling processes in this thesis capture the internal geometry of the accretion layers as well as geological trends. Curvilinear grids are constructed between major erosional surfaces where a grid transformation scheme is used to transform the curvilinear coordinates into orthogonal coordinates for geostatistical simulation. The grid transformation allows flexibility in performing statistical simulation in rectangular coordinate while honoring the curvilinear geometry of the point bar. An entire point bar model contains a series of accreting curviplanar grids. Geological modeling is done independently for each grid. The geology captures key trends that make up the heterogeneities in the model. The point bar model created is based on a modern point bar in the Brazos River. Data from thirty-three wells are used in creating the reservoir model. Several distinct trends are observed. There is an upward decrease in sediment size in the point bar. An overall fining downstream trend is observed in the vertical slices of the point bar. Heterolithic bedding is observed where frequent layers of silt extend from the top to near the base analogous to outcrops. Mud and silt dominate the upward regions of the point bar while conglomerate and cobble are mainly present at the base. The flow simulation model investigated the effect of mud drapes and fining heterogeneities on the development of steam chamber in SAGD recovery. The mud drapes impeded the steam chamber rise. The steam chambers were initially divided into pockets based on the flow barriers present. After 1 years of production, the steam chamber reaches the top of the reservoir but continued to be separated by the mud/silt barriers. Comparing to the homogeneous case, the point bar model exhibited lower oil recovery.Item Reservoir modeling accounting for scale-up of heterogeneity and transport processes(2009-12) Leung, Juliana Yuk Wing; Srinivasan, SanjayReservoir heterogeneities exhibit a wide range of length scales, and their interaction with various transport mechanisms control the overall performance of subsurface flow and transport processes. Modeling these processes at large-scales requires proper scale-up of both heterogeneity and the underlying transport mechanisms. This research demonstrates a new reservoir modeling procedure to systematically quantify the scaling characteristics of transport processes by accounting for sub-scale heterogeneities and their interaction with various transport mechanisms based on the volume averaging approach. Although treatments of transport problems with the volume averaging technique have been published in the past, application to real geological systems exhibiting complex heterogeneity is lacking. A novel procedure, where results from a fine-scale numerical flow simulation reflecting the full physics of the transport process albeit over a small sub-volume of the reservoir, can be integrated with the volume averaging technique to provide effective description of transport at the coarse scale. In a volume averaging procedure, scaled up equations describing solute transport in single-phase flow are developed. Scaling characteristics of effective transport coefficient corresponding to different reservoir heterogeneity correlation lengths as well as different transport mechanisms including convection, dispersion, and diffusion are studied. The method is subsequently extended to describe transport in multiphase systems to study scaling characteristics of processes involving adsorption and inter-phase transport. Key conclusions drawn from this dissertation show that 1) variance of reservoir properties and flow responses generally decrease with scale; 2) scaling of recovery processes can be described by the scaling of effective mass transfer coefficient (Keff); in particular, mean and variance of Keff decrease with length scale, similar in the fashion of recovery statistics (e.g., variances in tracer breakthrough time and recovery); 3) the scaling of Keff depends on the underlying heterogeneity and is influenced by the dominant transport mechanisms. To show the versatility of the approach for studying scale-up of other transport mechanisms, it is also applied to derive scaled up formulations of non-Newtonian polymer flow to investigate the scaling characteristics of the apparent viscosity and effective shear rate in porous media.