Reservoir modeling

To remove some of the ambiguities in a heterogeneous oil reservoir, a three dimensional model of the reservoir would be constructed by application of newly introduced methods. The aim of this study is to define an accurate and efficient model of a complex reservoir in southwest of Iran and accurately derive the geological and geometrical properties of the reservoir for well location proposal. Seismic data in addition to well logs were used for that purpose. A corner point grid was used in this study, and a generic global scale-up method was combined with previous result for reservoir simulation. The final model pointed out the heterogeneous characterization of the reservoir and proved the advantage of combining these methods in constructing accurate and efficient reservoir models. According to these models, it is concluded that the reservoir has different productive zones in different members that was not cleared in the previous models.

The Mamuniyat petroleum reservoir in southwestern Libya is comprised of clean sandstones and interca-lated shale and sand facies that are characterized by spatial porosity variations. Seismic reflection data from the field exhibit relatively low vertical seismic resolution, side lobes of reflection wavelets, reflection interference , and low acoustic impedance contrast between the reservoir and the units underneath the reservoir, which make mapping those facies a difficult task. In the absence of broadband seismic data, optimizing frequency bands of bandlimited data can be used to suppress pseudoreflectors resulting from side-lobe effects and help to separate the clean sandstone facies of the reservoir. We have optimized the data based on our investigation of seismic frequency bands and used instantaneous frequency analysis to reveal the reflection discontinuity that is mainly associated with the reservoir boundary of the sandstone facies of the clean Mamuniyat reservoir. We also preformed rock-physics diagnostic modeling and inverted the seismic data using spectral-based colored inversion into relative acoustic impedance. The inverted impedance matches the up-scaled impedance from the well data and the inversion of relative acoustic impedance confirms the conclusion that was drawn from the instantaneous frequency results. The interpretation of facies distributions based on the instantaneous frequency was supported by the inversion results and the rock-physics models.

The change in the stratification pattern in Boadella Reservoir (Catalonia, Spain) due to the switch in water withdrawal was investigated for a 6-month period in the year 2000. A numerical one-dimensional model (DLM) was used to predict the thermal structure of the reservoir during the period of maximum water demand. The model was found to satisfactorily predict the basic trends of the thermal stratification of the water column of the reservoir. We used this model to investigate various possible water withdrawal scenarios. When thermal stratification has been completely developed, the location of the main thermocline coincides with the depth of the outlet, in the various withdrawal scenarios considered. The possible effect of the switch between outlets on the water quality of the reservoir is discussed.

Although reservoir characterization has been carried out by many researchers on the sedimentary package of the Bengal basin hydrocarbon province, integration of petrophysical and seismic sequence-based reservoir evaluation is rarely taken into account. This paper focuses on the identification of gas zones, reserve estimation and identification of new prospects in Srikail gas field within the eastern fold belt of Bengal basin integrating four wireline logs and 2D seismic data. Our study finds seven hydrocarbon-bearing zones (A, B, C, D, E, F and G) within the measured depth between 2429.5 and 3501 m. Petrophysical properties of seven hydrocarbon-bearing zones indicate that they are good quality reservoir sands. The gas horizons were mapped on seismic sections which reveal that the NW–SE anticlinal structure is largely affected by channels in the crest and western flank. The channels are infilled by fine-grained sediments which act as cap rock on northern and western parts of the stru...

Enhanced oil recovery (EOR) techniques are regaining interest as high oil prices have rendered such techniques economically attractive. Thermal EOR processes, which involve injection of heat into the reservoir, cause continuous alteration of the thermal characteristics of both reservoir rock and fluids that are seldom modeled in the heat and momentum transfer equations. In this study, the memory concept is employed to develop new dimensionless numbers that can characterize convective heat transfer between the rock and fluids in a continuous alteration phenomenon. The energy balance equation is employed to develop the heat transfer coefficient with the assumption that the rock achieves the fluid temperature instantaneously. The final form of the equation is written in terms of Peclet number and the three proposed dimensionless numbers. The results show that the proposed dimensionless numbers are sensitive to the absolute and effective thermal conductivities of the solid and fluids, average system heat capacity, and the hydraulic diffusivity of the fluid-saturated porous medium. One of the new numbers correlates with the Nusselt and Prandtl numbers, while the local Peclet number is found to be sensitive to memory. Since heat convection and conduction in porous media can now be explained through the proposed numbers with the memory concept, these numbers help characterize the rheological behavior of the rock-fluid system. This work will enhance understanding the effect of heat transfer on alteration of thermal conductivity during thermal recovery operations in a hydrocarbon reservoir.

A new R & D project to develop novel techniques for monitoring and modeling reservoir mass and heat flows is described. Integrated reservoir modeling and simulation technology is being developed which will improve the quality of mathematical reservoir models by taking account of geophysical data sets such as changes in micro-gravity, selfpotential, resistivity and seismic properties in addition to the conventional data sets usually employed in reservoir engineering studies. Computational feasibility studies of reservoir monitoring using geophysical survey techniques were performed based on a steady-state three-dimensional model of a hypothetical (but realistic and typical) geothermal reservoir system which was developed using a numerical reservoir simulator.

Abstract: Numerical simulation and modeling has dominated the computation-al sciences for decades. From Computational Fluid Dynamics (CFD) to Numer-ical Reservoir Simulation (NRS) most of the computational modeling is per-formed by numerically solving a set of nonlinear partial differential equations. When historical or experimental data exists, it is used to calibrate the computa-tional model. In this paper we propose a technology to use the historical and/or simulated to build data driven models. These data driven models that are devel-oped using artificial intelligence and data mining technologies have many uses some of which are: when the physics of the phenomenon being models is poorly understood and when the numerical modeling is computational expensive. In this paper we use modeling of petroleum reservoirs to introduce this new mod-eling technology based on pattern recognition capabilities of artificial intelli-gence and data mining.

The Naft Shahr oilfield is located along the boundary between Iran and Iraq. Considerable research activity in the study and design of horizontal oil and gas wells was performed in order to increase production efficiency and extraction of this field. In this investigation, well ...

Reservoir characterization plays a crucial role in modern reservoir management. It helps to make sound reservoir decisions and improves the asset value of the oil and gas companies. It maximizes integration of multi-disciplinary data and knowledge and improves the reliability of the reservoir predictions. The ultimate product is a reservoir model with realistic tolerance for imprecision and uncertainty. Soft computing aims to exploit such a tolerance for solving practical problems. In reservoir characterization, these intelligent techniques can be used for uncertainty analysis, risk assessment, data fusion and data mining which are applicable to feature extraction from seismic attributes, well logging, reservoir mapping and engineering. The main goal is to integrate soft data such as geological data with hard data such as 3D seismic and production data to build a reservoir and stratigraphic model. While some individual methodologies (esp. neurocomputing) have gained much popularity during the past few years, the true benefit of soft computing lies on the integration of its constituent methodologies rather than use in isolation. q

Petrophysical rock typing (PRT) and permeability prediction are of great significance for various disciplines of oil and gas industry. This study offers a novel, explainable data-driven approach to enhance the accuracy of petrophysical rock typing via a combination of supervised and unsupervised machine learning methods. 128 core data, including porosity, permeability, connate water saturation (Swc), and radius of pore throats at 35% mercury injection (R35) were obtained from a heterogeneous carbonate reservoir in Iran and used to train a supervised machine learning algorithm called Extreme Gradient Boosting (XGB). The algorithm output was a modified formation zone index (FZIM*), which was used to accurately estimate permeability (R2 = 0.97) and R35 (R2 = 0.95). Moreover, FZIM* was combined with an unsupervised machine learning algorithm (K-means clustering) to find the optimum number of PRTs. 4 petrophysical rock types (PRTs) were identified via this method, and the range of their ...

Geologic storage projects associated with large anthropogenic sources of greenhouse gases (GHG) will have lifecycles that may easily span a century, involve several numerical simulation cycles, and have distinct modeling teams. The process used for numerical simulation of ...

The development of enhanced geothermal systems using CO 2 (CO 2-EGS) is a promising idea for expanding geothermal energy production (especially in areas with scarce water resources) when large supplies of captured anthropogenic CO 2 may be available in the future. Implementing this concept relies on replacing the natural geothermal brine in the reservoir with injected CO 2 to achieve enhanced energy recovery, and raises the questions of the fate of dissolved salts in the brine as CO 2 dries out the system, and how any precipitated salt could affect fluid flow. In this case, a new TOUGH2 equation of state module (ECO 2 H) was used to simulate CO 2 injection in an EGS with a brine system comprised of H 2 O and NaCl. This so called CO 2-EGS reservoir is at a depth of 3.5-4.5 km with normal pressure (hydrostatic) and temperature (160-200 • C) gradients. A classic "five-well" geometry is assumed in our 706 m × 706 m × 1 km block, of which only one eighth of the area needs to be modeled due to symmetry. The fractured EGS reservoir was modeled using the multiple interacting continua (MINC) conceptual model with fracture spacing of 10 m. Dry CO 2 was injected at the bottom of the initially brine-saturated reservoir and hot fluids were produced from the top of the reservoir. Simulations show that the brine contained in the fractures is produced initially, and only a few weeks later, the CO 2 plume breaks through at the production well. The two-phase nature of flow at this time causes a reduction in flow rate. Fluid production increases again as the reservoir dries out and the injected CO 2 fills the fractures (and more slowly the matrix). As the produced fluid becomes single-phase CO 2 , energy production is enhanced. For salt mass fractions of the order of 0.01 (salinity of 10,000 ppm), total heat produced during the lifetime of the well (about 6 years) is 270% more than that achievable with H 2 O as the working fluid. This result is probably at the lower end of what had been previously suggested by Randolph and Saar (2011). Simulation results show that as the brine is driven out of the matrix by capillary pressure, H 2 O evaporates into the CO 2 plume and salt precipitates in the fractures clogging up the flow system. At the highest salt mass fraction modeled here (0.15), enhanced energy production is inhibited by halite precipitation in the fractures. Our simulations suggest that for low-salinity systems, significant clogging occurs close to the production well after less than 10 years, while at high salinities clogging occurs close to the injection well in less than one year. Even though clogging of the reservoir is an apparently inevitable consequence of the drying of the saline geothermal reservoir, the fact that clogging occurs in specific reservoir regions could imply that remediation strategies could be developed to mitigate clogging.

The persistence of atrazine, one of the most applied herbicides in corn cropping areas, in an aquatic environment is dependent upon environmental conditions, i.e. temperature, sunlight, and presence of microorganisms. As these conditions vary seasonally, accurate determination of a time-variable degradation rate is important for the prediction of its fate and transport in surface water. A mass balance was performed to estimate the time-variable transformation rate (or half-life) of atrazine in the Saylorville Reservoir, Iowa. Calculated atrazine concentrations were compared with field data to verify the estimated half-life, which agreed reasonably well with the trends of observed values. A significant inverse relationship between the half-life and the hours of sunlight was obtained, showing the effectiveness of photodegradation. Estimated annual atrazine budget showed that 60% of the atrazine transported into the reservoir exited unchanged via outflow releases, while 40% was by kine...

In the beginning of the field's exploitation, it was believed that where net gas thickness was greater, the associated production would also be greater. This assumption changed as time passed, as wells were found with similar net gas thicknesses but different production behavior. Available petrophysical studies at that time did not explain these differences, resulting in difficult reservoir analysis for the field. To characterize the formation in a more precise manner, an integral petrophysical analysis was conducted, using all available information (core, production, geology and seismic). The analysis identified zones with high content of calcareous cement which affected the quality of the reservoir and its production potential. A multi-mineral petrophysics model that considers the existing lithologic factors and its influence in the rocks’ properties was used to locate the calcareous intervals, thus helping to reduce economic risk and investment of time in the development of t...

This paper presents an overview of soft computing techniques for reservoir characterization. The key techniques include neurocomputing, fuzzy logic and evolutionary computing. A number of documented studies show that these intelligent techniques are good candidates for seismic data processing and characterization, well logging, reservoir mapping and engineering. Future research should focus on the integration of data and disciplinary knowledge for improving our understanding of reservoir data and reducing our prediction uncertainty.

In recent years reservoir characterization through the use of geostatistics has become an almost routine part of production geology. Many techniques are available within the broad title of geostatistics, having been developed in response to many types of problem. One characteristic feature of almost all techniques (Stochastic Indicator Simulation, Boolean [open quotes]object[close quotes] Modeling, Gaussian [and Truncated Gaussian] methods and

The use of CO 2 as a working fluid in place of formation brines in Enhanced Geothermal Systems (EGS) could allow, in addition to CO 2 sequestration, a more efficient recovery of reservoir heat for any given pressure gradient between injection and production wells. We simulate an idealized low-salinity brine-filled reservoir in which we inject CO 2. We produce heat from the extracted fluid that is at first just brine, later brine + CO 2 , and finally CO 2 only. As the CO 2 plume develops the aquifer dries out, precipitating salt and inducing clogging of the fractures in proximity to the production well. To mitigate this effect, we have simulated combined brine and CO 2 injection that, at specific mass fractions, doubles the life of the well but limits the rate of heat extraction. The total heat extracted over the life of the well is 40% larger than in the dry CO 2 case. Simulation of more realistic geologic settings with involvement of chemical reactions would be necessary to evaluate the feasibility of CO 2-EGS in any particular geothermal system.

Enhanced oil recovery (EOR) techniques are regaining interest as high oil prices have rendered such techniques economically attractive. Thermal EOR processes, which involve injection of heat into the reservoir, cause continuous alteration of the thermal characteristics of both reservoir rock and fluids that are seldom modeled in the heat and momentum transfer equations. In this study, the memory concept is employed to develop new dimensionless numbers that can characterize convective heat transfer between the rock and fluids in a continuous alteration phenomenon. The energy balance equation is employed to develop the heat transfer coefficient with the assumption that the rock achieves the fluid temperature instantaneously. The final form of the equation is written in terms of Peclet number and the three proposed dimensionless numbers. The results show that the proposed dimensionless numbers are sensitive to the absolute and effective thermal conductivities of the solid and fluids, average system heat capacity, and the hydraulic diffusivity of the fluid-saturated porous medium. One of the new numbers correlates with the Nusselt and Prandtl numbers, while the local Peclet number is found to be sensitive to memory. Since heat convection and conduction in porous media can now be explained through the proposed numbers with the memory concept, these numbers help characterize the rheological behavior of the rock-fluid system. This work will enhance understanding the effect of heat transfer on alteration of thermal conductivity during thermal recovery operations in a hydrocarbon reservoir.

Geologic storage projects associated with large anthropogenic sources of greenhouse gases (GHG) will have lifecycles that may easily span a century, involve several numerical simulation cycles, and have distinct modeling teams. The process used for numerical simulation of the fate of GHG in the subsurface follows a generally consistent sequence of steps that often are replicated by scientists and engineers around the world. Site data is gathered, assembled, interpreted, and assimilated into conceptualizations of a solid-earth model; assumptions are made about the processes to be modeled; a computational domain is specified and spatially discretized; driving forces and initial conditions are defined; the conceptual models, computational domain, and driving forces are translated into input files; simulations are executed; and results are analyzed. Then, during and after the GHG injection, a continuous monitoring of the reservoir is done and models are updated with the newly collected data. Typically the working files generated during all these steps are maintained on workstations with local backups and archived once the project has concluded along with any modeling notes and records. We are proposing a new concept for supporting the management of full-scale GHG storage projects where collaboration, flexibility, accountability and long-term access will be essential features: the Geologic Sequestration Software Suite, GS 3 .