Spatial Distribution Of Reservoir Properties Research Articles

Reservoir rock typing and electrofacies characterization by integrating petrophysical properties and core data in the Bangestan reservoir of the Gachsaran oilfield, the Zagros basin, Iran

The super-giant Gachsaran oilfield is situated in the Dezful Embayment of the Zagros basin. The main goal of this study is to characterize the reservoir rock types by integrating the available geological and petrophysical studies in the Bangestan reservoir along with adopting a way to figure out the optimal number of electrofacies codes. At the first step, the types of porosity and geological microfacies were studied by using 163 thin sections from the core samples. The microscopic studies revealed that fractures and intraparticle interstices are the most common porosities types. Also, they resulted in the identification of 4 microfacies in the Bangestan reservoir. In a complementary study, the Velocity-Deviation Log (VDL) was employed to determine the dominant pore types. By comparison of the VDL values and thin section studies’ results, it was deduced that high micro-porosities along with hairline fractures are the predominant pore types of the Bangestan reservoir. At the second step, the optimal number of reservoir rock types (RRT) was determined by using the concept of hydraulic flow units. Thus, six flow units were distinguished by utilizing the Flow Zone Indicator (FZI) method in which the reservoir properties were improved from RRT-1 toward RRT-6. In the third step, the data clustering analysis, known as the electrofacies analysis, was employed to identify the accurate petrophysical rock types based on the meaningful segregation of capillary pressure curves within each electrofacies code and then propagated in non-cored intervals and boreholes. In this research, an optimal number of 7 electrofacies were identified by employing the petrophysical curves including effective porosity (PHIE), bulk density (RHOB), sonic (DT), and water saturation (SWE), along with considering the number of reservoir rock types and the defined geological microfacies, as well as the relations of the available capillary pressure data within different electrofacies codes. The validity of the proposed electrofacies was scrutinized through petrophysical results including shale volume, water saturation, and effective porosity. In the end, the electrofacies codes were compared to the defined geological microfacies. Finally, this study shows that the correlation of capillary pressure data and electrofacies codes can be resulted in figuring out the optimal number of electrofacies codes. In addition, by trying to honor the link between geological microfacies, capillary pressure, and petrophysical curves, the constructed electrofacies model, as a suitable practical integrated rock typing method, can be the foundation of property modeling, guide the spatial distribution of reservoir properties in the 3D model, aids to model the dynamics of fluid flow more realistically in reservoir simulation phase, and ultimately be beneficial for further development and production decisions in the Bangestan reservoir of the Gachsaran oilfield.

RESERVOIR PROPERTIES OF BARREMIAN–APTIAN URGONIAN LIMESTONES, SE FRANCE, PART 2: INFLUENCE OF DIAGENESIS AND FRACTURING

Integrated sedimentological, diagenetic and structural analyses have been carried out on microporous and tight Urgonian (Barremian – Aptian) limestones in a study area in SE France in order to understand the influence of diagenetic changes and structural deformation on the spatial distribution of reservoir properties. A diagenetic history for the carbonates was established and was divided into phases which correspond to episodes of regional geodynamic activity. Petrographic (optical, SEM and cathodoluminescence microscopy), structural and geochemical (δ18O, δ13C) studies were carried out to characterize the cement phases in the carbonates, especially micrite and blocky calcite, and to investigate their relationship with episodes of fracturing.Eleven calcite cement phases and four micritic cement phases were identified in relation to the two main phases of structural deformation which affected the Urgonian limestones. A first phase of micrite cementation occurred early in the diagenetic history and was linked to early marine cementation at the tops and bases of depositional cycles during the Barremian. A major phase of micrite recrystallization, which generated microporosity in carbonates that had previously been preserved from early cementation, was followed by a first phase of blocky calcite which occluded intergranular pore spaces. The blocky cement formed in a shallow burial meteoric environment and contributed to the preservation of microporosity during late Durancian tectonism (Albian – Cenomanian). A second phase of blocky calcite is associated with fracture activation during latest Eocene (Priabonian) – Oligo‐Miocene extension.Reservoir rock‐types (RRTs) proposed in a previous study were consistent with the diagenetic characteristics and the results of δ13C / δ18O analyses. Microporous RRTs formed as a result of early to late shallow burial processes and display low δ13C values; whereas cemented RRTs developed both due to early marine cementation (with high δ13C values) and/or as a result of cementation related to fluid flow linked to the reactivation of faults and fractures. This suggests that some late diagenetic and microstructural processes were pre‐determined by early diagenetic changes in the carbonates. The resulting stratigraphic architecture consists of a vertical stacking of weakly fractured microporous limestone intervals alternating with highly fractured, cemented limestone units.

Multiresolution Grid Connectivity-Based Transform for Efficient History Matching of Unconventional Reservoirs

Summary Proper characterization of heterogeneous rock properties and hydraulic fracture parameters is essential for optimization of well spacing and reliable estimation of estimated ultimate recovery (EUR) in unconventional reservoirs. High resolution characterization of matrix properties and complex fracture parameters require efficient history matching of well production and pressure response. We propose a novel reservoir model parameterization method to reduce the number of unknowns, regularize the ill-posed problem, and enhance the efficiency of history matching of unconventional reservoirs. The proposed method makes a low-rank approximation of the spatial distribution of reservoir properties taking into account the varying model resolution of the matrix and hydraulic fractures. Typically, hydraulic fractures are represented with much higher resolution through local grid refinements compared to the matrix properties. In our approach, the spatial property distribution of both matrix and fractures is represented using a few parameters via a linear transformation with multiresolution basis functions. The parameters in transform domain are then updated during model calibrations, substantially reducing the number of unknowns. The multiresolution basis functions are constructed by using Eigen-decomposition of an adaptively coarsened grid Laplacian corresponding to the data resolution. Higher property resolution at the area of interest through the adaptive resolution control while keeping the original grid structure improves quality of history matching, reduces simulation runtime, and improves the efficiency of history matching. We demonstrate the power and efficacy of our method using synthetic and field examples. First, we illustrate the effectiveness of the proposed multiresolution parameterization by comparing it with traditional methods. For the field application, an unconventional tight oil reservoir model with a multistage hydraulic fractured well is calibrated using bottomhole pressure and water cut history data. The hydraulic fractures as well as the stimulated reservoir volume (SRV) near the well are represented with higher grid resolution. In addition to matrix and fracture properties, the extent of the SRV and hydraulic fractures are also adjusted through history matching using a multiobjective genetic algorithm. The calibrated ensemble of models are used to obtain bounds of production forecast. Our proposed method is designed to calibrate reservoir and fracture properties with higher resolution in regions that have improved data resolution and higher sensitivity to the well performance data, for example the SRV region and the hydraulic fractures. This leads to a fast and efficient history matching workflow and enables us to make optimal development/completion plans in a reasonable time frame.

THE STUDY OF THE PREDICTIVE ABILITY OF NUMERICAL AND ANALYTICAL MODELS (THE CASE OF MUTUAL WELL IMPACT EVALUATION)

The main purpose of any model is to provide an opportunity to study the model object and the processes running in it for obtaining the predictive characteristics, among other reasons. In this connection, it is important to know, which mathematical models can help in analyzing and supporting oil deposit development, in particular, in assessing the mutual influence of production and injection wells. The characteristic features of mathematical modeling of field development include the oil deposits being located in natural formations that cannot be directly observed, as well as the complex filtration processes taking place in the formations due to the formation structure. Therefore, the mathematical modeling of development can be both complex and simple. On the one hand, it may use complex numerical hydrodynamic models, based on the understanding of spatial distribution of reservoir properties, which have an opportunity for detailed description of filtration processes. On the other hand, the modeling may use relatively simple analytical models, which have no need to specify the spatial distribution of properties; yet, the description of filtration processes is significantly simplified in comparison with hydrodynamics. Therefore, the practical value of the modeling result depends on the right approach to modeling. The task of estimating the mutual influence of wells requires the choice of numerical or analytical model to be based on understanding of the predictive ability of the models under consideration. Since such ability depends both on the ability to describe filtration processes in detail and on the need to take into account the spatial distribution of reservoir properties, it is initially impossible to conclude, which model has the best predictive ability. It becomes possible to reveal the level of predictive ability when considering the problem of mutual well impact assessment for synthetic models of oil deposits. This article presents the results of studies in the case of ten synthetic models. Numerical hydrodynamic models and analytical CRM models were set up for “actual” data of well operation. Using the retrospective test method, the authors have shown that the analytical models have a higher predictive power than the numerical models.

Optimization Techniques for History Matching and Production Forecasting

Reservoir modelling and production forecasting can provide vital inputs to the efficient management of petroleum. Since the reservoirs are highly heterogeneous and nonlinear in nature, it is often difficult to obtain accurate estimates of the spatial distribution of reservoir properties representing the reservoir and corresponding production profiles. If an accurate model of a reservoir is built, it can lead to efficient management of the reservoir. This paper describes the mathematical modelling of oil reservoirs along with various optimization techniques applicable for history matching and production forecasting. Gradient based and non-gradient based optimization techniques viz. Simulated Annealing (SA), Scatter Search (SS), Neighborhood algorithm (NA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Ensemble Kalman Filters (EnKF) and Genetic Algorithm (GA) and their application to reservoir production history matching and performance are presented. The recent advancements and variants of these techniques applied for the purpose are also presented.

Facies, petrophysical and geochemical properties of gravity-flow deposits in reservoir analogs from the Itararé Group (late Carboniferous), Paraná Basin, Brazil

Abstract Since many reservoirs do not allow direct observation due to their depth and/or difficulty of sampling, studies of analogs have been commonly used as a tool to understand the spatial distribution of reservoir properties. The Parana Basin is 1.6 million km2 large and has two known petroleum systems. However, there are only 124 irregularly distributed wells drilled in the basin, among which 22 contain gas or oil shows and 10 have sub commercial accumulations. The Permo-Carboniferous Itarare Group, due to the exploration history, is the best exploratory target in the basin because it has thick intervals of sandstones with moderate to good reservoir quality and also because it often lies directly on gas-prone source rocks of the Devonian Ponta Grossa Formation. In order to increase knowledge about Itarare Group reservoirs, as well as to better understand its heterogeneities, this study aims to integrate petrophysical data with facies and facies associations using both outcrop and cores from shallow wells in southeastern Parana Basin. By doing this it is expected to fill a gap of quantitative data in previous studies on reservoir analogs in the Itarare Group. Cores and outcrops were analyzed in sandstones in order to integrate surface and subsurface data, and to understand the lateral continuity according to stratigraphic correlations. Equipment such as gamma-ray spectrometer, portable x-ray fluorescence, and a minipermeameter were used for the acquisition of quantitative data. Sedimentological description of cores and outcrops as well as thin section description were also carried out. The facies with the greatest reservoir potential are medium to fine-grained, massive (Sm) and normally-graded (Sg) sandstones. In one outcrop locality (Rio dos Cedros), the Sg facies presents the best reservoir properties such as secondary porosity of 32% and average permeability of 1439 mD. The geochemical data allowed evaluating the gamma-ray variation in relation to chemical elements, such as iron oxide. In outcrop, API radiation is higher in relation to the cores, as well as Al2O3 and Fe2O3. These values are related to the large amount of intraclasts and cementation by iron oxides-hydroxides. Despite in the great amount of iron presents in the Rio dos Cedros samples, the porosity is mainly secondary, generated by the feldspars dissolution. The correlation between the cores and outcrops allowed the evaluation of the influences of mass transport deposits in the petrophysical properties of sandstones. In cores, sandstones interbedded with these deposits have high permeability, but it is not possible to evaluate its lateral continuity. In outcrops it was possible to observe that these deposits affect lateral continuity, permeability and porosity. We conclude that the best reservoir facies in the Itarare Group will be associated with sites within the basin that are away from the slope region and the influence of mass-transport processes.

Petrophysical Properties Distribution Modelling of an Onshore Field, Niger Delta, Nigeria

This research is based on the modelling of petrophysical parameters distribution of an onshore oil field in Niger Delta. The methodology involves the construction of 3-D grids that represent the reservoir geometry, accompany by property modeling where the 3-D grids were populated with petrophysical properties (porosity, water saturation, net to gross ratio, facies and permeability). The objective is to construct a 3D-dimensional reservoir model that characterizes and evaluate reservoirs in an onshore oil field, Niger delta. Three-dimensional grid and geophysical logs of 4 oil boreholes were used to characterize the delineated reservoirs. Two lithologies and two reservoirs were delineated from the logs. The lithologies are sandstone and mudstone which are arranged in alternation representing the Agbada Formation of the Niger Delta. The calculated petrophysical parameters for the two reservoirs in the four wells were used for estimating the properties distribution in the reservoirs. The petrophysical properties estimation and distribution was done with inverse distance weighting of deterministic techniques of modeling. The calculated porosity values for the two reservoirs range from 0.061 to 0.30 with an average of 0.185. The permeability of the two reservoirs ranged from 110 to 2394 mD. The calculated water saturation and net to gross ratio of the two reservoirs range from 0.23-0.57 with an average of 0.4 and 0.44-0.87 with an average of about 0.61 respectively. The porosity, permeability, water saturation and net to gross ratio and facies models show uniform distribution within the reservoirs. From the models, it can be inferred that the reservoir properties within the central part of the field are very good. It is, therefore, advisable that wells should be drilled in the central region to investigate the presence of oil. The results of this study have shown the effectiveness of 3D reservoir modeling as a tool for understanding the spatial distribution of reservoir properties. The results can be used as a guide for evaluating future performance and production behavior of the reservoirs.

Spatial stochastic modeling of sedimentary formations to assess CO2 storage potential.

Carbon capture and sequestration (CCS) is a technology that provides a near-term solution to reduce anthropogenic CO2 emissions to the atmosphere and reduce our impact on the climate system. Assessments of carbon sequestration resources that have been made for North America using existing methodologies likely underestimate uncertainty and variability in the reservoir parameters. This paper describes a geostatistical model developed to estimate the CO2 storage resource in sedimentary formations. The proposed stochastic model accounts for the spatial distribution of reservoir properties and is implemented in a case study of the Oriskany Formation of the Appalachian sedimentary basin. Results indicate that the CO2 storage resource for the Pennsylvania part of the Oriskany Formation has substantial spatial variation due to heterogeneity of formation properties and basin geology leading to significant uncertainty in the storage assessment. The Oriskany Formation sequestration resource estimate in Pennsylvania calculated with the effective efficiency factor, E=5%, ranges from 0.15 to 1.01 gigatonnes (Gt) with a mean value of 0.52 Gt of CO2 (E=5%). The methodology is generalizable to other sedimentary formations in which site-specific trend analyses and statistical models are developed to estimate the CO2 sequestration storage capacity and its uncertainty. More precise CO2 storage resource estimates will provide better recommendations for government and industry leaders and inform their decisions on which greenhouse gas mitigation measures are best fit for their regions.

Reservoir permeability prediction by neural networks combined with hybrid genetic algorithm and particle swarm optimization

ABSTRACTReservoir characterization involves describing different reservoir properties quantitatively using various techniques in spatial variability. Nevertheless, the entire reservoir cannot be examined directly and there still exist uncertainties associated with the nature of geological data. Such uncertainties can lead to errors in the estimation of the ultimate recoverable oil. To cope with uncertainties, intelligent mathematical techniques to predict the spatial distribution of reservoir properties appear as strong tools. The goal here is to construct a reservoir model with lower uncertainties and realistic assumptions. Permeability is a petrophysical property that relates the amount of fluids in place and their potential for displacement. This fundamental property is a key factor in selecting proper enhanced oil recovery schemes and reservoir management. In this paper, a soft sensor on the basis of a feed‐forward artificial neural network was implemented to forecast permeability of a reservoir. Then, optimization of the neural network‐based soft sensor was performed using a hybrid genetic algorithm and particle swarm optimization method. The proposed genetic method was used for initial weighting of the parameters in the neural network. The developed methodology was examined using real field data. Results from the hybrid method‐based soft sensor were compared with the results obtained from the conventional artificial neural network. A good agreement between the results was observed, which demonstrates the usefulness of the developed hybrid genetic algorithm and particle swarm optimization in prediction of reservoir permeability.

Relation between stratigraphic architecture and multi-scale heterogeneities in carbonate platforms: The Barremian–lower Aptian of the Monts de Vaucluse, SE France

Understanding the relationship between multi-scale sedimentary heterogeneities and the stratigraphic architectures of carbonate platforms improves the interpretation of paleoenvironmental evolution in time and space. Such an approach improves the prediction of the spatial distribution of reservoir properties within carbonate stratigraphic units.The reservoir-scale stratigraphic anatomy and the growth history of a Barremian–Aptian carbonate platform (Monts de Vaucluse, SE France) was based on 1) high-resolution measured sections on outcrops, 2) detailed microfacies analyses, 3) paleoenvironmental interpretations, 4) biostratigraphy using rudist bivalves, foraminifera, calcareous algae, and locally echinoderm and ammonites, and 5) sequence stratigraphic interpretations with a special focus on the identification of discontinuity surfaces with a significant stratigraphic correlation potential and critical environmental meaning.The platform succession consists of subtidal (mainly infralittoral) with rare inter- to supratidal deposits. Thirty types of elementary facies, grouped in 12 facies associations, have been defined. The vertical and lateral changes in paleoenvironments together with the development of remarkable stratigraphic surfaces, such as subaerial exposures, marine erosional surfaces, and drowning surfaces, allow the definition of five stratigraphic sequences ranging from the late Barremian to the earliest Aptian.These depositional sequences can be grouped into two distinct carbonate sedimentary systems characterized by specific sedimentary profiles and skeletal and non-skeletal components: 1) a carbonate platform with stronger hydrodynamic gradients, rimmed by a narrow belt of high energy deposits with corals and rudistid rudstone facies and 2) a carbonate ramp dominated by orbitolinids fine-grained facies, including an elongated high energy oolitic shoal. The two-dimension architecture of the depositional sequences (dimensioned geometries, thickness and facies variations) and the morphology of the shelf reflect a strong interaction between tectonic (differential subsidence), sediment production and global environmental conditions. At the km-scale, the “Gorges de la Nesque” stratigraphic motif could represent a nested stratigraphic structure within the large-scale model, which could be implemented for up-scaling petrophysical properties from the well to a full-field model. The association of coral facies to the rudist-dominated system in the Provence platform is a very clear proxy of the polarity of the carbonate platform and is critical for subsurface facies-property modeling based on well data. Finally, at the global scale, the stratigraphic architecture and the step-wise drowning events of the Provence platform confirm and document the precursor events associated with environmental perturbations that affected the carbonate factory prior the Oceanic Anoxic Event 1a (OAE1a).

Reservoir properties and petrophysical modelling of carbonate sand bodies: outcrop analogue study in an epicontinental basin (Triassic, Germany)

AbstractThis paper represents the second part of an integrated study that is focussed on the development and distribution of reservoir bodies and properties in epeiric carbonate systems. It is based on outcrop analogue data from Triassic ‘layer-cake’ carbonates in the South German Basin, which were deposited along an epicontinental, very gently inclined carbonate ramp. The reservoir facies consists of skeletal and oolitic carbonate grainstones (Φmax 23%, Kmax 700 mD), which are organized in a pronounced hierarchy of stratigraphic cycles. Based on outcrops, cores, gamma ray (GR) logs and thin sections, a high-resolution, geocellular 3D facies model was generated, which covers the area of a Middle East giant gas field (25×36 km). The spatial distribution of reservoir properties was systematically investigated on different scales. The lateral distribution of reservoir properties remains in the same order of magnitude for hundreds of metres, within in the same stratigraphic position. However, on a kilometre scale, facies bodies, diagenetic trends and thus reservoir properties show gradual lateral changes. Vertically, in contrast, properties change commonly on a decimetre scale and are largely controlled by stratigraphic cycles. Petrophysical modelling enhanced the understanding of key factors and processes controlling both reservoir quality and quantity.

Morphological patterns of Aptian Lithocodium-Bacinella geobodies: relation to environment and scale

Lithocodium aggregatum and Bacinella irregularis are now extinct, shallow marine life forms of unknown taxonomic origin. Forming part of the tropical platform biota during much of the Mesozoic, these organisms experienced bloom periods and temporarily replaced rudist–coral assemblages during parts of the Early Aptian. Within the limitations of time resolution, this ‘out-of-balance’ facies is coeval with the Oceanic Anoxic Event 1a-related black shale deposition in oceanic basins but the triggering factors remain poorly understood. Here, a platform-wide comparison of Lithocodium–Bacinella geobodies and morphotypes from the Sultanate of Oman is presented and placed in its environmental, bathymetric and physiographic context. Lithocodium–Bacinella geobodies reach from kilometre-scale ‘superstructures’ to delicate centimetre-sized growth forms. Clearly, scale matters and care must be taken when drawing conclusions based on spatially limited observational data. Whilst the factors that cause Lithocodium–Bacinella expansion should probably be considered in a global context, regional to local factors affected growth patterns in a more predictable manner. Here, the unresolved taxonomic relationship remains the main obstacle in any attempt to unravel the response of Lithocodium–Bacinella to specific or interlinked environmental parameters as different organisms respond differently to changing environment. Acknowledging these limitations, the following tentative patterns are observed: (i) Lithocodium–Bacinella tolerated a wide range of hydrodynamic levels and responded to differences in energy level or physiographic settings (margin, intrashelf basin, inner platform) by obtaining characteristic growth forms. (ii) Lithocodium–Bacinella favoured low-sediment input but had the ability to react to higher sedimentation rates by enhanced upward growth; a feature perhaps pointing to a phototrophic metabolism. Circumstantial evidence for continuous growth within the upper-sediment column is debated. (iii) The availability of accommodation space had a direct influence on the maximum size of geobodies formed. (iv) Fluctuating nutrient levels and sea water alkalinity may have affected the growth potential of Lithocodium–Bacinella. Understanding the relationship between Lithocodium–Bacinella morphogenesis on a wide range of scales and local environmental parameters allows for better prediction of the spatial distribution of reservoir properties and also results in an improved interpretation of palaeoenvironments. This study might represent a useful first step in this direction.

Spatial Distribution of Reservoir Properties Using Seismic Attributes Correlated to Log Properties: ABSTRACT

Reservoir description maps have traditionally been generated using seismic data in succession with well log data. Integrating well logs with seismic maps in a separate step is not taking advantage of all the information contained within a 3-D data set. This paper describes a technique that statistically correlates seismic and log data to produce integrated maps of reservoir frequencies with increased resolution and confidence. The procedure involves first matching 3-D seismic with borehole seismic data. Then a statistical correlation is attempted between seismic attributes including amplitude, impedance, velocity, etc., and log properties such as porosity, water saturation, net to gross, bulk water volume, etc. at the well intersections. A multivariant function of the correlations is then derived. This function is applied to seismic data to produce reservoir property maps. This technique has been applied to 3-D data from Indonesia. Results and problems in estimating the functional relationship are discussed.

Prediction Of Uncertainty In Reservoir Performance Forecast

Abstract Geostatistical models are used to provide equally probable reservoir descriptions that honour available data of a given reservoir. The differences between these descriptions provide an indication of reservoir uncertainty due to lack of information. Transferring this uncertainty into the reservoir performance forecast would require flow simulation of a large number of these equally probable descriptions. The spread in the response derived from the flow simulation measures its uncertainty. However, this approach is not a viable option in most cases because it would require excessive amounts of computer time. A new approach for transferring geological uncertainty is presented. Each reservoir description is first ranked using a Fast Simulator (FS) rather than the Comprehensive flow Simulation (CS). A few selected descriptions are then processed through the CS to generate an approximate probability distribution of tile reservoir production response. This approach yields a considerable saving in the computer time over the use of the CS alone. This approach is tested using a waterflood example in a quarter of a five-spot. A standard black-oil type simulator is used as the CS and a tracer model is used as the FS. Approximate probability distribution of production parameters (water breakthrough rime, cumulative oil recovery and cumulative water-oil ratio) are generated by selecting just five reservoir descriptions among 100, and processing them through the CS. The approximation is tested by running the CS on all 100 cases to generate the reference probability distributions. The tracer concentration at the producer provided very good results with a 90% reduction in computer time over the use of the CS for all 100 descriptions. Introduction Many complex geological processes, such as sedimentation, erosion, migration, compaction and diagenesis produce complex spatial distributions of reservoir properties. Rock type, porosity, permeability, fault occurrence, degree of cementation, and hydrocarbon saturation are some of these properties. However, the exact conditions that result from these complex geological processes are never known e.xacrly. This spatia [distribution of reservoir properties generally presems some degree of Variability, often shared with a complex geological architecture. Moreover, in practice, samples obtained represem only a very small fraction of [he whole reservoir volume, resulting in incomplete knowledge about the reservoir structure at all scales. For all these reasons, it is not advisable to consider only one single reservoir description or image and describe the spatial distribution of reservoir properties in a purely deterministic manner. Rather, a statistic.a1 treatment of the variables involved is desirable one that recognizes the lack of knowledge or uncertainty associated with any description selected. The geological uncertainty can be determined through the differences between many equally probable reservoir descriptions generated using a geostatistical technique known as slochastic simulation(l,2). Each of the images reproduces a prior measure of spatial continuity (covariances) and may be conditioned to honour available data, such as, core and log data, well test, geophysical and geological interpretation, etc. The variables that should mostly be described using probablistic techniques are those that influence the amount, position, accessibility and flow of fluids through the reservoir (e.g. lithofacies or flow unit distributions, porosity, permeability, and fault occurrences).

Silurian Reef in Michigan Basin--Stratigraphic-, Facial-, and Reservoir-Properties Analysis: ABSTRACT

The Belle River Mills gas field (China Twp., St. Clair Co.), discovered in 1961 and since 1965 utilized as an underground gas-storage reservoir, is one of 42 known reefs of Niagaran (Middle Silurian) age in southeastern Michigan, 36 of which are oil or gas producers. The reef is an elongate pinnacle structure, about 2 mi long and 0.75 mi wide. It attains a maximum relief of 420 ft with slopes ranging from 10 to 30°. Three major growth phases are recognized: (1) biohermal, consisting of skeletal (crinoid, bryozoan, coral, and tabular stromatoporoid) wackestone and packstone rudites and arenites; (2) organic reef, consisting of a reef core (massive stromatoporoids, corals, and algae?) and associated interbedded and interfingering lithofacies of backreef skeletal wackestone rudite, burrowed mudstone and laminite, and coarse skeletal forereef talus; and (3) supratidal cover complex, composed of stratified algal stromatolites, flat pebble conglomerates, oncolites, and burrowed pelletal mud. The mound developed to a height of 150 ft in quiet, relatively deep water. The reef grew in turbulent water, attaining a height of 300 ft above the surrounding sea floor. Reef growth stopped as a result of shallowing and increased salinity, which led to the deposition of the supratidal complex. A conglomerate composed of algal stromatolite pebbles and boulders derived from the supratidal complex phase is present 400 ft below the reef crest at the base of the offreef Salina Group. It is covered by the A-1 anhydrite (15 ft) and the A-1 carbonate (120 ft) which both wedge out toward the reef walls. The A-1 carbonate is finely laminated, finely crystalline dolomite devoid of fossils, in places pelletal with algal mats, birdseye, and desiccation features and having an abundance of various textural forms of anhydrite. It is indicative of a very shallow-marine, partly supratidal environment. The conglomerate and the environmental interpretation of the A-1 carbonate demonstrate that the offreef sequence is post-reef in age and that the reef was subaerially exposed during the deposition of the overlying units. Dolomitization and diagenetic processes of leaching and reprecipitation associated End_Page 848------------------------------ with this exposure period destroyed much of the original depositional texture. A statistical data-reduction method was developed and used to construct a representative picture of the spatial distribution of reservoir properties. There is a correlation between stratigraphic and reservoir facies, markedly modified by diagenesis. End_of_Article - Last_Page 849------------

Simulation of High Relief Reservoirs, Rainbow Field, Alberta, Canada

A comparison of the three-dimensional and one-dimensional models for both natural depletion and crestal gas injection shows that for high relief reservoirs, a one-dimensional model is adequate for many reservoir engineering applications. Introduction The Rainbow field of northwestern Alberta was discovered in 1965 and currently contains 44 separate reef reservoirs with areal extents up to 4,600 acres, and productive oil pay zones up to 600 ft. Production is from the Rainbow member of the middle Devonian Keg River formation, which occurs at a depth of approximately 6,000 ft. Average porosity values range from 4 to 15 percent and typical average values of vertical and horizontal permeability are 40 and 200 md, respectively. Excellent reservoir communication has allowed wide well spacing ranging from 160 to 640 acres. Oil in place varies from less than 10 million bbl in the smaller pinnacle reefs to 260 million bbl in the larger atolls. Reef buildups in the Rainbow area are shown schematically in Fig. 1. In the Rainbow field, many different types of secondary recovery projects have been initiated, including bottom-water drive, projects have been initiated, including bottom-water drive, crestal gas injection and vertical downward miscible slug displacement. Gravity drainage controls all recovery mechanisms, and typical predicted recovery factors are 55 percent for natural depletion, 65 percent for gas or water injection and 95 percent for percent for gas or water injection and 95 percent for miscible displacement. Under the Alberta oil proration system, allowables are distributed among pools on the basis of recoverable reserves. Therefore, to define allowables in the Rainbow reservoirs it is necessary to evaluate accurately the recoverable reserves for both primary depletion and secondary recovery projects. To perform these studies, several mathematical reservoir simulators were used. These included one-, two- and three-dimensional, three-phase, compressible and incompressible models. The use of these different models for studying various depletion mechanisms for many different reservoirs offered a unique opportunity to evaluate their speed, cost and areas of application. This paper discusses the use of geology in defining the spatial distribution of reservoir properties; some particular problems that arose in the simulation of particular problems that arose in the simulation of Rainbow-type reefs and the methods used to solve some of these problems. The functional steps in the multidimensional simulation of performance are shown graphically in Fig. 2. Use of Geological Studies to Define the Spatial Distribution of Reservoir Properties The wide well spacing in the Rainbow area led to extensive use of geological studies to define the spatial distribution of reservoir rock properties (porosity, permeability, capillary pressure, relative permeability) for use in mathematical models. Detailed permeability) for use in mathematical models. Detailed studies have been performed on the reefs in the Rainbow area, including the examination of data from 45 wells in 13 separate reservoirs and 15,000 ft of core. These studies revealed the presence of 14 geological rock types or lithofacies. The 14 rock types represent six depositional environments: basin, forereef, organic reef, backreef, lagoon and shoal. JPT P. 1399