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Collaborating Authors
SPE Asia Pacific Oil and Gas Conference
Abstract A novel normalised plot technique is developed for reservoir characterisation and reserves estimation. This method is based on the Buckley-Leverett and Welge's fluid displacement theories. The theories suggest that under ideal conditions a normalised plot of oil recovery as a function of water or gas (displacing phase) throughput is independent of rate, drainage volume, and geometry of the system. This implies that in a homogeneous reservoir, well by well normalised recovery plots should collapse to one curve. In reality, well performance is influenced by reservoir heterogeneity, drive mechanism (bottom vs edge drive), gravity, and well locations. Therefore, the normalised curves do not often match and that leads to reservoir dynamic characterisation. The normalising factor, sweep volume, is related to the recoverable reserves (RR) that we seek to estimate. This paper presents the theoretical background of the technique and illustrates its application by presenting two field examples. Introduction Use of decline curve analysis for reserves estimation is a common practice in the petroleum industry. Reference 3 presents a summary discussion of the decline methods. However, these techniques are not based on any physical theories. Furthermore, decline analysis assumes constant operating conditions (choke size, artificial lift, etc), which is hardly ever met in field production operations. Experience has shown that analysis by exponential decline generally yields a conservative forecast (also known as a 'buyer's forecast'). On the other hand, hyperbolic extrapolation often results in an optimistic estimate ('vendor's forecast'). The applicability of the above techniques is basically a matter of convenience. The x-cut plot analysis, a second method, is based on fractional flow theory, but the assumption that a semi-log plot of permeability versus saturation data would be a straight line is not valid in all reservoirs and fluid flow systems. A third approach used in the industry is cumulative oil versus cumulative liquid (representing water influx in a water drive reservoir) production plot. Since drainage volumes and consequently recoverable reserves generally vary from well to well, such plots cannot be compared on a one to one basis. A meaningful comparison is achieved if the above conventional cumulative plots are normalised by their respective reservoir drained volumes (hence the name normalised plot). Mathematical Basis In 1942 Buckley and Leverett presented the basic equation for describing immiscible displacement in one dimension (also known as Frontal Advance Equation). In 1952 in another paper of fundamental importance, Welge enlarged upon Buckley and Leverett's work and derived an equation that relates the average displacing fluid saturation to that saturation at the producing end of the system. Welge also determined that pore volumes of cumulative injected fluid is equal to the inverse of the slope of the tangent on fractional flow curve. The above mathematical developments have become the basis of performance predictions of incompressible fluids in one- dimensional systems. In reality, reservoir fluids (particularly gas) are compressible and flow dynamics hardly occur in a linear system. Kern has shown application of the Buckley and Leverett equation to reservoir geometry to predict gas flooding performance. A generalised form (variable cross-section) of Frontal Advance displacement developed by Latil shows that the Buckley-Leverett theory is applicable in a reservoir as long as the displacement takes place in a porous medium whose geometry leads to the equipotentials and isosaturations being superimposed. The pore volume traversed by iso-saturation in a variable geometry reduces to a distance travelled in a linear system. P. 603
- Oceania > Australia > Northern Territory (0.47)
- Oceania > Australia > Queensland (0.29)
- Oceania > Australia > South Australia > Eromanga Basin (0.99)
- Oceania > Australia > Queensland > Eromanga Basin > Tintaburra Field (0.99)
- Oceania > Australia > Northern Territory > Eromanga Basin (0.99)
- (7 more...)
Abstract A bounded reservoir with wells producing at constant rate will exhibit pseudosteady-state behavior after the end of typically short-lived infinite-acting and transition flow periods. This study develops a new approach for directly calculating pseudosteady-state flow behavior without solving the full time-dependent form of the diffusivity equation. This approach can be applied to the linearized forms of the diffusivity equation for either single-phase liquid or gas flow. A finite-element method is used which allows for spatially-dependent reservoir properties, complex reservoir geometries, and multiple wells. The first part of this paper presents a verification of the approach by comparing results for some regularly-shaped systems against full-transient solutions reported in the literature. For the simulation of field-scale problems with multiple wells of differing production rates, a well model based on a near-wellbore approximation of the pseudopressure distribution during pseudosteady-state is introduced to reduce the concentration of elements near wells. The second part of the paper demonstrates application of the direct pseudosteady-state concept to actual reservoir problems. To account for rate changes during extended production periods, the pseudosteady-state equation was solved successively for each flow period and combined with an overall reservoir material balance analysis. Results from this study show that this approach provides a fast and accurate method for modeling the long-time behavior of various types of reservoirs under depletion conditions. The approach is particularly applicable to single-phase volumetric gas reservoirs. Introduction One or more wells produced at constant rate in a closed reservoir will exhibit monotonic pressure decline. Pressure decline behavior can be characterized as occurring in four distinct regimes. The first regime (early time) is dominated by wellbore storage effects. During this time, pressure response is largely determined by the unloading of fluids from the wellbore with little actual response due to flow into the wellbore from the reservoir. This time generally lasts from a few minutes to a few hours. The second flow regime is sometimes called infinite-acting time, during which well response is essentially the same as that of a well being produced from an infinite reservoir. For radial flow, infinite-acting time is characterized by a semilog straight line of well flowing pressure vs. time. Most pressure transient tests are analyzed during this time period. Infinite-acting time ends when the well response begins to deviate from infinite-acting behavior due to a nearby barrier, discontinuity, or reservoir property change in the vicinity of the well. Once the first nearby boundary affects the well response, it enters what is sometimes called transition time. Stabilized time begins at the end of transition time, after all reservoir boundaries, discontinuities, etc. are fully felt and the well approaches a quasi-steady flow regime sometimes called semisteady or pseudosteady-state flow. The onset of stabilized time may be anywhere from a few hours to even many months. For most reservoirs stabilized time begins at times that are much shorter than the life of the reservoir. The day-to-day operation of most wells in depletion reservoirs is governed by relationships during this time. This paper addresses the depletion behavior of closed systems during pseudosteady state. For a well produced at constant rate, pseudosteady state is characterized by pressures in the reservoir declining everywhere in the reservoir at the same rate. This means that the pressure profile lowers uniformly throughout the reservoir and that mass fluxes everywhere are constant with time. P. 589
Abstract In the design of an optimum enhanced oil recovery operation an accurateareal and vertical mapping and analysis of the simulation results plays a fundamental role. In this type of analysis not only should the finer details of the reservoir be considered, but also the grid system superimposed over the domain of interest should exhibit compatibility and consistency with the actualphysics of the problem. This will help in accurate characterization of the reservoir and the ongoing physical processes within the domain of interest. The implications of the aforementioned statements are investigated with the aid of developing a 3-D field scale steam injection simulator. The multi-phasemass and energy transport equations are based on compositional balances. In themodel the gravitational and capillary forces are accounted together with the viscous flow phenomenon. A fully implicit treatment is used at the multi-block production and injection wells to couple the wellbore to the reservoir. A fully implicit technique is utilized in the solution of the nonlinear system of equations. A systematic analysis of the areal and vertical distribution of parameterssuch as pressure, temperature, phase saturations and composition is conducted. Through this detailed analysis the ever-changing relative effects of the various dominant forces on the establishment of production mechanisms and ultimately on the oil recovery are studied. The fully implicit formulation, which assumes all the reservoir parametersand operational parameters to be functions of all primary variables identified, makes it possible to focus on any parameter and investigate its effects on oil production. Both qualitative and quantitative implications of capillary pressure on the oil production are observed to be strong functions of the size and uniform nature of the grid constructed over the computational domain. The proposed model provides some significant insight into the displacement mechanisms and aids us in developing a comprehensive understanding of the nature and magnitude of the forces and controlling parameters. Such an understanding will help in the design of specifics of a recovery operation.
Abstract This paper presents a case study in the use of 3D seismic and reservoir simulation to plan infill drilling at a new platform in the B-Field. The B-Field, located about 60 miles Northeast of Jakarta, Indonesia, has about 200 million barrels of recoverable oil with production since 1975. A prior B-Field platform set in 1990 resulted in only 8% oil, expected reserves. Aquifer water had swept through that region in response to offset production since the original delineation well had been drilled. With that failure a multidisciplinary team was formed to evaluate B-Field potential. A petrophysical analysis and reservoir zonation of 107 wells formed the basis for a black-oil simulator, built with 10 layers and covering 10,000 acres. While the simulator reservoir description was built and the model history matched, a 3D seismic survey was shot over the region. Interpretation of the 3D seismic showed significant structural differences from the 2D seismic. Upcoming infill drilling of five wells from a single platform was re-planned based upon the new 3D seismic interpretation and the simulated aquifer water fronts. One well, designed as a geo-resistivity steered horizontal well in a 10' thick pay horizon, targeted a region that the 2D seismic survey had indicated was below the oil-water contact. This paper details aspects of the simulator construction, history match, forecasting and the infill drilling planning process and results. The simulation-based oil rate and reserves forecasts are compared to prior results using volumetric methods. Infill drilling and production results were found to match reservoir simulation-based expectations. The horizontal well produces at the highest oil rate for this platform, and the other wells also show good production. Additional platforms and infill drilling opportunities are being investigated in B-Field. Introduction The B-Field in Offshore Northwest Java (ONWJ), Indonesia began oil and gas production in 1975. Figure 1 is a locator map for the B-Field in ONWJ, Indonesia. The B-Field produces from 10 to 12 productive sandstone horizons under moderate aquifer support. In 1987, extension exploration Well BJ-1 was drilled on the southern flank of the field and discovered oil. A platform jacket and deck were set in 1990. Three more wells were drilled from the BJ platform and tied into the production gathering system. The BJ platform wells produced at initial water cuts of 40% to 90%. Actual reserves were 8% of the forecast used to justify BJ platform installation and drilling. The BJ platform deck and jacket have been moved to another structure and the wells permanently abandoned. Figure 2 is a plan map for B-Field. To improve understanding of the B-Field, a core, log, and geological interpretation were begun in 1993 jointly with the company technology center in the USA. A core-based petrological study was performed. Open hole log data from 107 wells dating back to 1968 were loaded to a computer database and a petrophysical log interpretation was developed using the core data. After log and core interpretation was complete, interpreted hydraulic flow units were correlated into a cohesive reservoir zonation. In 1994 a multi-disciplinary team was formed composed of development geologists, geophysicists, production, drilling and reservoir engineers. The charter of this group was to re-evaluate B-Field potential and to examine the northerly BM platform planned to be installed in mid-1995 (see Figure 2). A 3D seismic acquisition program was initiated in B-Field with interpretation planned to influence development at the BM platform. The intention was to integrate these efforts with a full field reservoir simulator to predict well performance and avoid another BJ-platform experience. P. 581
- Geology > Geological Subdiscipline (0.88)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock (0.48)
Development and Applications of a Three Dimensional Voronoi-Based Flexible Grid Black Oil Reservoir Simulator
Kuwauchi, Yusuke (Mitsui Oil Exploration Company) | Abbaszadeh, Maghsood (Japan National Oil Corporation) | Shirakawa, Shinji (Arabian Oil Company) | Yamazaki, Noboru (Fuji Research Institute Corporation)
Development and Applications of a Three Dimensional Voronoi-Based Flexible Grid Black Oil Reservoir Simulator Yusuke Kuwauchi, Mitsui Oil Exploration Company, Maghsood Abbaszadeh, SPE, Japan National Oil Corporation, Shinji Shirakawa, SPE, Arabian Oil Company, Noboru Yamazaki, Fuji Research Institute Corporation Copyright 1996, Society of Petroleum Engineers, Inc. Abstract This paper presents a methodology for the development and applications of an efficient three dimensional black oil reservoir simulator based on the Voronoi flexible gridding scheme combined with the control volume finite element (CVFE) algorithm. This simulator is named VERDI3D. The flexible Voronoi gridding scheme allows for better representation of reservoir heterogeneity features and better modeling of complex flow behavior around wells, and the CVFE method reduces numerical dispersion effects. The reliability of VERDI3D is verified by comparing the simulation results with analytical solutions for several difficult reservoir problems such as finite conductivity faults, distributed discontinuous thin fractures or stochastic barriers, and horizontal wells with random hydraulic fractures. Based on these case studies, it is shown that VERDI3D could be used for well test analysis, recovery prediction and modeling of displacement processes in highly heterogeneous reservoirs. Efficient gridding schemes are possible in VERDI3D for heterogeneous reservoirs where there exist multilateral horizontal wells, fractures or faults of any geometry and Orientation, and other complex geologic features. Introduction Large and homogeneous reservoirs are less likely to be discovered these days, therefore, small and heterogeneous reservoirs must be developed on commercial basis. Unilateral and multilateral horizontal wells have become popular and hydraulic fracturing in tight reservoirs is utilized actively for improved recovery. Along with these technical advances, the importance of accurate evaluation of more complex reservoirs with highly accurate reservoir simulators is recognized more than before. The technique of reservoir simulation is based on discretizing fundamental partial differential equations of flow through porous media according to a certain discretization scheme and in a certain domain, and solving for the discretized forms using various numerical techniques. Throughout the past years, different expressions have been developed for the discretization of flow equations. It is clear that fine grids are needed around wellbores to represent the rapid changes in pressure gradient that occur around them. In an orthogonal cartesian grid configuration, this method, however, would require that cells which are far away from wells also to be fine in order to follow the configuration of fine cells around the wells. Therefore, the aspect ratio of some grids could be large which would decrease the calculation accuracy. To avoid the problem, local grid refinement method has been developed. Because in simulation schemes the direction of pressure gradient is perpendicular to the grid boundary, the influx along the grid direction is dominant and the direction of grids should therefore affect the results. Specifically, it is impossible to represent accurately the influx situation around wells using the difference grid. To solve the problem, hexagonal or radial grids which are less sensitive to orientation effects are attempted in regions around wells. However, the accuracy of calculation is decreased in radial grids, depending on how far away from the well the radial gridding is continued. Also, it is impossible to simulate adequately a horizontal well without adjusting the direction of grids to coincide more realistically with the direction of the horizontal well, something that is particularity difficult in certain ordinary gridding schemes. Because of the above problems, flexible gridding and Voronoi gridding methods have been introduced in the simulation of petroleum reservoirs to offer flexibility, accuracy and practicality.
Abstract In the development planning studies of the Natuna gas project, a three-dimensional, two-phase reservoir simulation model of the Natuna gas field was used for evaluation of the gas reservoir and as a planning tool. A detailed sequence stratigraphic study of the gas field that incorporated seismic, well log and core data provided the basis for the geological model used in the reservoir simulation model. The objective of the development planning studies was to determine production well locations, production well drilling schedules, the total number of wells required, the timing for the installation of wellhead compression equipment and the gas production profile for the field as a function of time. The reservoir is estimated to be able to sustain a 2,400 million standard cubic feet per day (Mscf/d) methane production rate for 30 years or more. Introduction The Natuna gas field, located in Indonesian waters in the Natuna Sea, is estimated to have an original raw gas-in-place volume of over 200 trillion standard cubic feet (Tscf) making Natuna the largest undeveloped gas reserve in South East Asia. A three-dimensional, two-phase (gas and water) reservoir simulation model of the Natuna gas field was used for evaluation of the gas reservoir and as a basis for planning of the Natuna project. A detailed geological model of the carbonate formation provided the reservoir description used in the simulation model. The simulation model was used in development planning studies to determine production well locations, the well requirements versus time, total number of wells required, the timing for the installation of wellhead compression equipment and the gas production profile for the field as a function of time. Both initial field development and full-field development options were investigated with the reservoir simulation model. These studies are also the basis for the estimated ultimate recovery from the Natuna field. Field Overview The Natuna gas field lies approximately 140 miles northeast of Natuna Island and 218 miles northwest of Kalimantan (Fig. 1). Natuna Island is about 375 miles northeast of Singapore and 700 miles north of Jakarta. The water depth in the field area is approximately 475 feet. The discovery well, AL-1X, was drilled on the crest of the AL-Structure in 1973 by the Italian oil company AGIP and encountered approximately 5,250 feet of porous, gas-bearing carbonate section. After acquiring the concession for the area in 1980, Esso conducted a 2-D seismic survey over the D-Alpha Block and drilled four additional wells on the AL-Structure: wells L-2X, L-3X, L-4X, and L-SX (Fig. 2). The crest of the gas reservoir is at a depth of approximately 8,625 feet subsea. A gas-water contact was established by three wells (L-2X, L-3X, and L-SX) at a depth of 14,000 feet. The total volume of gas in the reservoir is estimated to be 222 Tscf. The composition of the gas is about 71% carbon dioxide, 28% methane plus heavier hydrocarbons, 0.5% hydrogen sulfide and 0.5 % nitrogen. The estimated gas recovery from the field is about 75% which would yield 46 Tscf of recoverable hydrocarbon gas. Reservoir Description The Natuna gas reservoir is interpreted to be an isolated, dome-shaped carbonate build-up structure (carbonate platform and reef complex) approximately 15 miles long and 9 miles wide. P. 567
- North America > United States (1.00)
- Asia > Indonesia > Natuna Sea (1.00)
- Asia > Indonesia > Jakarta > Jakarta (0.24)
Abstract This paper discusses a methodology for estimating permeability from well logs, based on conventional core and log data. The work was done on a small set of wells containing a glauconitic sandstone reservoir in the Barrow Sub-basin offshore, Western Australia. Core porosity and permeability data were used to determine porosity-permeability transforms and to subdivide the "greensand" into various groups within two sub-units. Electrofacies patterns and decision functions were determined to establish a link to permeability transforms in order to identify sandstone groups and to obtain porosity and permeability from well logs where cores were not available. Estimates of permeability were found to be more accurate than using other methods. In this technique, permeability transforms were obtained not only by considering unique relationships between porosity and permeability but also grain size and sorting et al. The results of this work have been encouraging and the study is now being extended on a regional basis. Introduction In formation evaluation, it is generally essential to obtain realistic values of permeabilities from well logs because core-based permeability data are often not available either because of bore hole conditions or due to the high cost of coring. For many years, attempts have been made to estimate permeability from well logs. Much literature has been published on the subject and a number of methods and models are being used to achieve this goal. Two categories of equations are generally available. One category contains the so-called 'standard methods' such as Wyllie and Rose (1950), Timur (1968), Coates and Dumanoir (1973) and some modified forms of these. They are based on establishing empirical relationship (formulas or models) which are functions mainly of porosity, permeability, irreducible water saturation or clay content. However, none of these is generally applicable from field to field, well to well or even zone to zone without making adjustments to constants or exponents, or introducing compensations. Moreover, the accurate determination of irreducible water saturation and clay content from well logs is not an easy task. Alternatively, there are 'statistical methods' such as are described by Nicolaysen (1991), Sinha (1994), Johnson (1994) and others. They attempt to establish a direct statistical relationship between log responses and permeability, or use a data base to relate permeability to log responses on a field wide basis. The methods utilise relationships which are implicit in the data to arrive at results. No predetermined equations are required, and results are obtained by statistical inference. The subject reservoir of this study is an extensive, marine transgressive, and glauconite-rich formation. It was deposited during a southward-progressing marine transgression over deltaic topset sands during the Early Cretaceous. The glauconitic sandstone is mineralogically complex. The main mineral components include quartz, glauconite, siderite, dolomite, calcite, feldspar, kaolinite, pyrite, and their alternation products. Quartz, glauconite, feldspar and siderite generally are the most abundant minerals and occur together in most of the Mardie lithofacies Porosity (helium injection) and permeability were determined on 139 core plugs on 4 wells cored in this area. They indicate that porosities are medium to high (from 13.9% to 29.7%), that permeability ranges from 0.01 md to 47 md throughout the sandstone in the two main sub-units and that there is poor correlation between porosity and permeability. Traditional methods for estimating permeability from log responses are not applicable in the Mardie Greensand. P. 561
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Sandstone (1.00)
- Geology > Mineral > Silicate > Tectosilicate (0.95)
- North America > United States > Texas > Permian Basin > Yeso Formation (0.99)
- North America > United States > Texas > Permian Basin > Yates Formation (0.99)
- North America > United States > Texas > Permian Basin > Wolfcamp Formation (0.99)
- (34 more...)
Abstract This study was intended to produce a synthetic index derived from statistical analyses of well data to indicate the reservoir qualities of various drilled intervals, and ultimately to link log response information to seismic traces for 2D/3D reservoir modelling and reserve estimations. Statistics and multivariate statistics were applied to wireline logs from four wells in the Kupe South Field, Taranaki Basin, New Zealand combined with traditional well log interpretation. The results indicates:synthetic wireline indices show good correlation with core and sidewall core data; four sand zones (A-D) of the Paleocene Farewell Formation identified in some previous studies cannot be statistically recognised; closely similar index features were shown in Kupe South-2 and Kupe South-3, while the other wells had different index values; and there exits a possibility of using synthetic wirelog index correlated with seismic traces for further 2D and 3D reservoir modelling and reserve estimation. This paper was presented by J. Pang at the 1996 SPE Asia Pacific Oil and Gas Conference held in Adelaide, Australia, 28โ31 October 1996. Introduction Kupe South Field is a gas condensate/oil field located in the South Taranaki Graben Zone of offshore Taranaki Basin, New Zealand. It was discovered in 1986 with the drilling of Kupe South-1 and four additional wells have since been drilled. The field is one of the most prospective fields for production within the country. The reservoir for the Kupe South Field is the Paleocene Farewell Formation and the sediments are of fluvial origin that were deposited on an alluvial plain in meandering to braided stream environments with minor tidal component. The sandstones of the reservoir are dominantly medium to coarse grained with subordinate mudstones and clay, and unconformably overlain by Oligocene marine shale. Reservoir quality and distribution are key factors for reserve estimation and field development plans. Alluvial deposits characteristics show rapid changes of lithologies laterally and vertically. This makes direct comparison and correlation of units from the limited available data extremely difficult and sometimes even impossible. Use of statistical techniques may provide an effective method for predicting reservoir quality and distribution. This study was intended to examine the use of wireline logs to determine the reservoir qualities of logged intervals by means of statistic and multivariate statistic techniques, and if possible, to examine the possibility of linking wireline log information to seismic data for 2D/3D reservoir modelling. Log responses (gamma ray, sonic, density and resistivity) of four wells (Table. 1) in the Kupe South Field were chosen in this study to examine statistical feature of different Paleocene intervals. Method of Study Data Preparation Based on the core, sidewall core and well completion reports, four reservoir groups were defined. Group one is good quality sandstone and group four is non-reservoir shale and clay. The reservoir quality of group two is similar to group one but contains more shaly sands or shale/clay thin layers. Group three includes shaly sandstone or siltstone with poor reservoir quality. Sixty-six drilling intervals were selected as samples after the exclusion of some intervals with extreme log responses, and each sample was designated to a different reservoir group (Table. 2). Five attributes of wireline records (GR, DT, RHOB, LLD and LLS) were collected for each interval. Statistical parameters, such as the mean, were used as sample values. This is because that individual wireline record does not represent the interval log response and variation of the log record is common within an interval for the same lithology section; P. 535
- Oceania > New Zealand > North Island (0.82)
- Oceania > Australia > South Australia > Adelaide (0.24)
- Research Report > New Finding (0.35)
- Research Report > Experimental Study (0.35)
Abstract Water saturation (Sw) in shaly sand formations has been a subject of debate for many years and several equations have been introduced for the estimation of Sw. In the present study, several equations for the estimation of Sw are applied in the Late Carboniferous - Early Permian kaolinite-bearing Tirrawarra Sandstone, an important oil reservoir in the Cooper Basin. The results from Archie and Waxman-Smits equations display a good correlation with measured core water saturation. Plots of water saturation from the Archie equation with water saturation from the other equations show that the Archie and Waxman-Smits equations are approximately the same (r2=98%). As can be expected, due to the low cation exchange capacity (CEC) of Tirrawarra Sandstone, the second part of the Waxman-Smits equation concerning shale conductivity is very small. As a consequence, the values of Sw from the Waxman-Smits equation are very close to those from the Archie equation. Petrographical studies indicated that kaolinite patches in the Tirrawarra Sandstone are water wet. In this case, the formation resistivity is a function of formation water in macro-porosity and irreducible water associated with kaolinite micro- porosity. In other words, when kaolinite is electrically inert, the whole rock can be considered as a clean sandstone which obeys the Archie law. Because resistivity logs cannot recognise free water within the macroporosity from bound water associated with clay minerals, calculated water saturation includes both free and irreducible water. As the irreducible water associated with kaolinite minerals is not expelled during production, some intervals of kaolinite-rich sandstones, which may never produce water, may be bypassed as non-productive zones. A new equation is introduced for estimation of effective water saturation. The equation is based on the integration of resistivity and sonic logs with image analysis data for wells in the Moorari and Fly Lake fields, where obtaining the volume of clay is difficult and unreliable. This equation, which reduces calculated water saturation by about 10% for the Tirrawarra Sandstone, is likely to be applicable to other kaolinite-bearing sandstones. Introduction Water saturation (Sw) is one of the most important petrophysical parameters required for reserve calculation. In clean sandstones, estimation of water saturation is rather simple due to the lack of electrically-conductive materials such as clays. The presence of clays in the shaly sandstones which display high conductivity (Ref. 1) makes estimation of water saturation complicated. In this paper, factors affecting conductivity of shaly sandstones are reviewed and some of the common equations which are used for calculation of water saturation are applied to the Tirrawarra Sandstone and a new equation to estimate water saturation in kaolinite-rich sandstones is introduced. Basic Concepts Electrical conductivity of a rock depends on several variables including, conductivity of rock components, conductivity of pore fluid, fluid saturation and formation factor (F). In clean sandstones, the conductivity of rock components is zero and electrical conductivity is a function of conductivity of pore fluid, fluid saturation and formation factor. In shaly sand formations, the electrical conductivity of rock components can not be considered zero, as clay minerals provide additional conductivity (Ref. 1). In these sorts of formations, conductivity of the clay minerals should also be estimated. Formation Factor. Formation factor was first introduced by Archie (Ref. 2) and defined as the ratio of the conductivity of brine to the conductivity of fully saturated clean sandstone: P. 539
- Oceania > Australia > South Australia (0.91)
- Oceania > Australia > Queensland (0.61)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Sandstone (1.00)
- Geology > Mineral > Silicate > Phyllosilicate (1.00)
- Oceania > Australia > Queensland > Cooper Basin (0.99)
- Oceania > Australia > South Australia > Cooper Basin > Moorari Field (0.94)
- Oceania > Australia > South Australia > Cooper Basin > Fly Lake Field (0.94)
- Oceania > Australia > South Australia > Cooper Eromanga Basin > Tirrawarra Field (0.89)
- Well Drilling > Drilling Fluids and Materials > Drilling fluid selection and formulation (chemistry, properties) (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Exploration, development, structural geology (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management (1.00)
Abstract We generate model random porous media which give a realistic representation of the complex microstructure observed in porous rocks. The freedom in specifying the parameters of the model allows the modeling of petrophysical media with diverse pore morphologies. The model qualitatively accounts for the principal features of a variety of sedimentary rocks. We derive the conductivity and permeability for the model porous materials. Excellent agreement with experimentally measured properties of sedimentary samples is obtained. The agreement provides a strong hint that it is now possible to correlate effective physical properties of rocks to microstructure. Introduction Rocks are heterogeneous. From a microscopic viewpoint the pore geometry is complex and difficult to enumerate. Determination of the precise solid-fluid boundary in anything but the simplest rocks is a difficult, if not impossible, task. For this reason many believe a quantitative approach to the problem might never be attained. Yet, understanding the inter-relationship between rock microstructure and its expression in geophysical and petrophysical data is necessary for enhanced characterisation of petroleum reservoirs. When studied at a macroscopic level, correlation of rock properties to rock characteristics have been noted. In particular, transport properties (conductivity and permeability) of porous rocks have been correlated to the volume fraction of pore space (porosity) of the solid. An empirical equation that links the conductivity of a brine saturated rock (r) to the porosity was first proposed by Archie: (1) Here F is the formation factor, w is the conductivity of the brine, is the porosity of the porous media and m the cementation exponent. Most experimental and theoretical work has been devoted to establishing the correlation variables m and C for different classes of rock. In these equations all the explicit microstructural information describing the porous solid is subsumed in the porosity and details of the microstructure are ignored. Changes in bulk porosity alone cannot explain the main features of the conductivity data. Microstructural parameters relative to the porous network must be included in a detailed analysis of the transport properties of rocks. Past theoretical attempts to relate macroscopic physical properties to a description of microstructure of the porous material have been limited. Most methods use oversimplified representations of the pore structure for which properties can be analytically evaluated. Examples include simple micro-porous models (dilute spheres, cylindrical tubes, periodic media) and effective medium approaches. These models do not explicitly account for microstructure. Therefore, to correlate the model to experimental data, these models must incorporate parameters which are poorly defined (e.g. shape factors). A major factor in attempts to understand the macroscopic behaviour of porous solids is the ability to generate, and to characterize, realistic model microstructures. In this paper we describe a model which gives a realistic representation of general porous media microstructure. The model is based on level cuts of a Gaussian random field with arbitrary spectral density. The freedom in specifying the parameters of the model allows the modeling of petrophysical media with diverse pore morphologies. The model qualitatively accounts for the principal features of a wide variety of sedimentary rocks. We calculate the conductivity and permeability for the model porous materials. Excellent agreement with experimentally measured properties of sedimentary samples is obtained. The agreement provides a strong hint that it is now possible to correlate effective physical properties of rocks to microstructure. P. 551