The effects of rock structural properties on porosity and penneability may be considered as generally well known, being particularly critical when modeling tight sands and limestones. Nevertheless, such effects have been slow to fmd their way into reservoir simulators. These effects are frequently even more important for fractured horizons where 10-20 porosity per cent changes, and/or several orders of magnitude change in penneability, can be observed under changing reservoir stress conditions. Rocks with weak tensile properties are particularly vulnerable to stress change. These include diatomite, chalks, and overpressured Gulf Coast shales.Less well known is the dependence of relative penneability on stress. Moreover, the effects of relative penneability and capillary pressure in the fractures themselves need to be accounted for.Production in naturally fractured reservoirs is limited by the exchange rates of oil and gas between matrix blocks and fractures. Naturally fractured simulators which use the conventional dual porosity fonnulation fail to resolve gradients in the matrix blocks unless some type of sub-gridding (subdomains) is used. This lack of resolution at the matrix/fracture interface leads to significant errors in production rates when modeling oil recovery from fractured reservoirs.

A sub domain formulation for modeling naturally fractured reservoirs is presented. "Representative Matrix Blocks" are subdivided into rectangular rings and layers to enhance pressure and saturation gradient resolution within the blocks. Improved description of matrix capillary and gravity forces can be achieved through this formulation. A three phase coupled implicit algorithm incorporates pressure dependent gas/oil capillary pressure, fracture permeability, and fracture porosity. Segregated and dispersed fracture fluid options are given, and field-scale simulations of primary depletion, water injection and gas injection are presented.Naturally fractured simulations with matrix block discretization can yield significantly different production forecasts from those without internal discretization. Quarter five-spot, low permeability waterfloods show differences in cumulative oil recovery as large as 35 percent. For small blocks, or moderate matrix permeability, differences in simulated oil rate are less than 10 percent.The dependence of gas/oil capillary pressure on pressure is shown by example to have a large effect on oil production rate. Jones' relations l7 between pressure and fracture porosity and permeability lead to modest changes itl oil rate when compared with constant fracture properties. At early times fracture permeability reduction decreases oil rates, while fracture porosity variation leaves oil rates unaffeded.Segregated fluid flow ill the fractures leads to smaller matrix/fracture fluid transfer rates, and hence lower oil recovery. A dispersed water phase in the fracture is exposed to larger matrix surface area,' creating additional opportunity to exchange itself with oil contained within the matrix block.

WELCOS is a robust, three-dimensional, three-phase well coning simulator that couples the well rate equation to the reservoir flow equations. This strong coupling allows well rate to be determined simultaneously with reservoir pressures and saturations. The flexibility obtained permits the use of dynamic constraints on well rates, resulting in a highly stable model. The model may be used to obtain the maximum well productivity for a given set of physical limitations and regulatory constraintse.g., minimum surface pressure, maximum allowed GOR, WOR, water rate, gas rate, etc. The model can function either as a production well or an injection well and, in general, may be used to "tudy any singlewell behavior.This paper describes a strongly coupled formulation and discusses its utility in relation to other implicit models. The linearization of the nonlinear finite difference equations and solution of the resulting linear equations are discussed. Example field applications are included to show the utility of user-supplied production constraints in determining well performance.

A high level screening has been performed of UKCS oil fields to identify the most likely LSWF candidates utilising screening criteria with a focus on kaolinite clay content. The screening results suggest that approximately 57% of the fields have 6 % or higher kaolinite clay content. Of these fields 26 % were water-wet and 74 % were mixed-wet in terms of wettability. This suggests that a significant number of fields would fall within the eligibility for consideration of LSWF EOR although their suitability will depend on field maturity (current recovery factor and facilities constraints). The difficulty in applying LSWF in tertiary mode unlike secondary mode, is in obtaining a reasonable prediction of how the reservoir is likely to respond. The question of core availability and quality has been raised in a number of studies in terms of LSWF and electrical property testing. We propose a methodology which can be applied to compensate for the lack of usable core based on petrophysical log response. The logs can be utilised to determine the clay types present (including fractions) from which the cation exchange capacity can be calculated. Selected compositions from anonymised field data from core was used to provide quality control the log derived values. The most likely recovery mechanism, multi-component ion exchange (MIE), requires the input of key electrical properties into the models (cation exchange capacity, reactive surface area, activation energy and mineral fraction) in order to predict the response of the reservoir to LSWF. In this study the effect of clay content on the reservoir response was modelled indirectly by altering the cation exchange capacity relative to the clay mineral fraction present in the reservoir to determine its effect. Utilising a mechanistic modelling approach, homogeneous Cartesian models were run in the compositional finite difference reservoir simulator GEM to assess the impact on oil recovery. The simulated coreflood tests reveal that under secondary LSWF recovery was 68.4 % compared to 63.6 % for formation water (high salinity). The conservative nature of the relative permeability curves limited the incremental recovery. An analysis of the tertiary recovery utilising a coreflood based on Fjelde et al. (2012) revealed that cation exchange impacts the predicted recovery by up to 2.65 % OOIP for the range of 5 - 30 % clay content. Given that the recovery under tertiary conditions is considered in the literature to be between 6 and 12 %, this is significant and highlights that if idealised data is selected rather than real field data, then significant potential exists to under or over-predict the incremental recovery.

This paper describes ALPURS, a new three-dimensional, three-phase, strongly stable, black oil simulator. ALPURS is capable of modeling reservoirs with complex rock properties and well production/infection controls. It can simulate reservoirs with large permeability contrasts, very active gravity segregation, and high flux rates. It rigorously adheres to well production/injection strategies that may be production/injection strategies that may be selected from a number of permissible options. The model couples the three-phase flow equations with the constraints imposed on individual wells. It derives stability from a simultaneous solution for all unknowns. The paper presents the linearization the nonlinear finite-difference equations and describes the solution of the resulting linear equations. Finally, it discusses various field oriented features of ALPURS and illustrates, by examples, two features important to several major reservoirs located in various parts of the world. Introduction ALPURS is a three-dimensional, three-phase, multiwell, black oil reservoir simulator that uses a strongly coupled, fully implicit method to solve simultaneously for all unknowns. Strong coupling requires that all cell and well equations for the entire grid system be solved simultaneously. Appendix B gives a proposed terminology to categorize reservoir simulators, including a definition of strong coupling. The principal use of ALPURS has been to model difficult problems such as high flux rates, gas resaturation, and gravity segregation. The original design called for a flexible, "user-proof" model that satisfies rigorously the individual well or well group constraints selected by the user. In addition to the usual features of, constant voidage, constant rate, or fixed flowing bottomhole pressure, the model would be required to optionally produce wells or well groups at prescribed GOR, GLR, and WOR. The design also called for automatic selection of constraints in such a way that none could be violated. For example, the user should be permitted to operate a well at a fixed oil rate until a specified GOR is reached. At that time he night elect to shut in the well, or to operate at the specified GOR, or some alternate constraint. Similar options would be required for GLR and WOR. Any number of constraints could be requested simultaneously. The model would operate the well to satisfy all constraints. For physically contradictory ones, the model would terminate the job. All design goals were met. The result is a simulator that handles difficult problems and production strategies without user intervention. production strategies without user intervention. There is no need for trial-and-error runs with varying well parameters to satisfy desired constraints. ALPURS accounts for reservoir heterogeneity rock compressibility, gravity, gas in solution in the oil and water phases, variable bubble-point pressure (gas resaturation), hysteresis in relative permeability data, tubing string pressure drop, and permeability data, tubing string pressure drop, and flash surface separation calculations. It is applicable to three-dimensional, three-phase studies. Fewer phases and/or dimensions can be modeled. The utility of ALPURS is enhanced further by modern concepts of well flow equations. These include the pseudo gas potential function, skin factor to account for damage or improvement, non- Darcy flow effect, flow restriction due to restricted entry such as partial penetration, and effect of the shape of the well's drainage area and its location within the drainage area. ALPURS has been used to study three-dimensional water and gas injection, above and below the saturation pressure, using CDC Cyber 172 and 175 computers. The strongly coupled method is computationally more expensive than a sequential formulation. But it has several offsetting advantages. Increased stability permits larger time steps than for sequential methods, especially far difficult problems. The coupling of the well constraints problems. The coupling of the well constraints yields a more reliable model than previously reported in the literature.