Reservoir Characterization Process Research Articles

A cell-centered multipoint flux approximation method with a diamond stencil coupled with a higher order finite volume method for the simulation of oil–water displacements in heterogeneous and anisotropic petroleum reservoirs

The simulation of fluid flow and transport in heterogeneous and anisotropic oil and gas reservoirs poses a great challenge from the numerical point of view, due to the modeling of complex depositional environments, including inclined laminated layers, channels, fractures and faults and the modeling of deviated wells, making it difficult to build and handle the Reservoir Characterization Process (RCM), particularly by using structured meshes (cartesian or corner point), which is the current pattern in petroleum reservoir simulators. Under certain hypotheses, the mathematical model that describes the fluid flow in petroleum reservoirs includes an elliptic equation with heterogeneous, possibly discontinuous, coefficients for the pressure field and a non-linear hyperbolic equation for the saturation field. In the present paper, these equations are solved via an Implicit Pressure Explicit Saturation (IMPES) procedure. To solve these equations, we use a full cell-centered finite volume formulation. The pressure equation is discretized by a non-orthodox Multipoint Flux Approximation Method with a Diamond type stencil (MPFA-D) and used for the first time for the solution of two-phase flow problems in heterogeneous porous media. It is very robust and capable of reproducing piecewise linear solutions exactly by means of a linear preserving interpolation with explicit weights that avoids the solution of locally defined systems of equations. For the solution of the saturation equation, we use a Monotone Upstream Centered Scheme for Conservation Laws (MUSCL) method based on a gradient reconstruction obtained by a least square technique in which monotonicity is reinforced by an appropriate slope limiter. The method can be used with general polygonal meshes, even though we restrict ourselves to conforming triangular and quadrilateral grids. In order to validate and show the robustness of our formulation, we solve some problems including heterogeneous and anisotropic reservoirs and displacements with high mobility ratios. Our results compare well with others found in literature.

Measuring Porosity and Permeability From Drill Cuttings

This article, written by Technology Editor Dennis Denney, contains highlights of paper SPE 111286, "Advances in Measuring Porosity and Permeability From Drill Cuttings," by R. Lenormand, SPE, IFP, and O. Fonta, Geopetrol, prepared for the 2007 SPE/EAGE Reservoir Characterization and Simulation Conference, Abu Dhabi, UAE, 28-31 October. The paper has not been peer reviewed. Drill cuttings can provide quick and useful information for reservoir characterization, especially when cores are not available. Several petrophysical properties can be determined from cuttings: porosity, permeability, and transverse-relaxation-time (T2) nuclear-magnetic-resonance (NMR) distributions (related directly to the pore-size distribution). Results are presented for porosity and permeability measurements on cuttings with diameters of approximately 0.5 mm and for a field test. Introduction Early determination of rock petrophysical properties is needed during the reservoir-characterization process because it affects estimates of reserves (porosity and saturation) and of well deliverability (permeability). Generally, well logs provide a good estimate of porosity and saturations along the wellbore, but permeability is more difficult to obtain. Cuttings are used routinely by mud loggers to build the "master log" of the geological description of the drilled formation. Hydrocarbon indices are determined from cuttings to identify the reservoir levels. Although rock-cutting material comes directly from the reservoir, few applications of porosity and permeability characterization are reported in the literature. The full-length paper details the methods used for porosity and permeability determinations from cuttings and presents results from tests on crushed cores. The main result is accurate determination of porosities for 0.5-mm-diameter cuttings for permeability of less than 1 md. The porosities and T2 NMR data measured on real cuttings from a well in the Paris basin are presented and compared to log results. Porosity Measurement on Cuttings The methods for measuring porosity on cuttings are the same as those for cores when the cutting size is larger than 3 mm. For smaller cuttings (most cases), the best results are obtained by use of a centrifuge or a porous plate to remove the interstitial liquid with a controlled capillary pressure. Porosities were measured to within 1 to 2 p.u., even for flat cuttings with diameters of approximately 1 mm and thickness of 0.5 mm collected during the field case. Improved Methods. To improve measurement accuracy for cutting sizes down to 0.5 mm, most of the existing methods were tested. A porous-plate method provided the most consistent results and is detailed in the full-length paper. The saturated cuttings are placed in a tube set on its end on the porous plate. Vacuum is applied through the plate to remove interstitial liquid and partially desaturate the plate. Then, the porous plate pulls the remaining interstitial liquid with a controlled capillary pressure. When the excess water is removed, the cuttings no longer stick together and move freely like dry samples.

Aplicação de técnicas de estatística multivariada na definição da litologia a partir de perfis geofísicos de poços

The definition of lithology in petroleum wells from analysis of multiple geophysics logs has an important role in the reservoir characterization process. As a matter of fact, from the definition of lithology is possible to build lithological models that can be filled with their respective petrophysical properties and, ultimately, they can be used in flow simulators in order to study the field’s behavior. Usually in the wells, only a little part of it is studied by core samples, mainly because the elevated costs in extract the samples from it. However, in the wells, some geophysical logs are running in all extension of it. With these logs, we have an indirect indication of the rocks that are present in the well. Therefore it is important to know and how to combine that information in a joint analysis to define the lithology in the portions, of the well that have no core samples. Given this motivation, the aim of this work is applying multivariate statistics techniques to define from the geophysical logs available the lithology that are present in the specific well. With this work, it is possible to show that beyond the traditional techniques, such as the principal components analysis, there are other techniques, such as K near neighbor, which can provide satisfactory results and can be applied vastly in the reservoir characterization process.

Krigagem das proporções utilizando a krigagem da média: uma ferramenta auxiliar na modelagem de reservatórios

The proportion curves have an important role in petroleum geology. With this tool it is possible to define specific intervals for the dominant facies and, as result we can use the proportion curve as a trend in lithological modeling. However, when the proportion curves are generated they don’t consider the well influence and the location of the wells. When we consider those information is possible to generate a more effective proportions curves. So, the main aim of this paper is to present a new technique to generate the proportion curves based in the mean kriging. The main advantage of this methodology is that the well location and his influence zone are considered in the process. This methodology indicated a efficient way to generate the proportion curves that can be used to support in a decisive way the reservoir characterization process linking to the lithological modeling.

Krigagem das proporções utilizando a krigagem da média: uma ferramenta auxiliar na modelagem de reservatórios

The proportion curves have an important role in petroleum geology. With this tool it is possible to define specific intervals for the dominant facies and, as result we can use the proportion curve as a trend in lithological modeling. However, when the proportion curves are generated they don’t consider the well influence and the location of the wells. When we consider those information is possible to generate a more effective proportions curves. So, the main aim of this paper is to present a new technique to generate the proportion curves based in the mean kriging. The main advantage of this methodology is that the well location and his influence zone are considered in the process. This methodology indicated a efficient way to generate the proportion curves that can be used to support in a decisive way the reservoir characterization process linking to the lithological modeling.

Application of Stochastic Inversion to Reservoir Characterization Process

To properly accomplish the reservoir characterization process in an effective way, it is necessary to integrate all the available information about the field in a consistent model. It is not an easy task to perform this integration in practice: it is necessary to use some specific methods such as seismic inversion. The seismic inversion is an efficient method to integrate both well-log and seismic data, obtaining a model that could be used in a forecasting process by numeric flow simulation. The seismic inversion can be achieved by several methods, which can be divided into two main groups: the deterministic methods (represented by the recursive inversion and constrained sparse-spike inversion) and the stochastic methods (represented by the geostatistical inversion). In this study, we show how stochastic inversion can improve the reservoir characterization process, by comparing its results with those obtained by deterministic inversion. The stochastic inversion can use a high sample rate that is close to the cell size of the reservoir model, implying that a more reliable model can be generated. The stochastic inversion method can also generate some basic statistics measurements that improve interpretations. Due to the great number of realizations generated during the process, we could also perform an uncertainty study on the reservoir model.

O papel da inversão para a impedância acústica no processo de caracterização sísmica de reservatórios

O processo de caracterizacao de reservatorios consiste na determinacao tridimensional e quantitativa da estrutura e das propriedades petrofisicas de um campo de petroleo. A utilizacao do dado sismico 3D neste processo tem se tornado cada vez mais comum principalmente na identificacao da forma e do tamanho dos corpos de areia que constituem o reservatorio. Porem em alguns casos como nos reservatorios turbiditicos de aguas profundas da Bacia de Campos, que sao caracterizados por uma complexa distribuicao dos corpos de areia e por camadas com espessura subsismica, a utilizacao do dado sismico convencional em amplitude pode acarretar serios erros na definicao de um modelo para o reservatorio. Para superar os problemas causados pela limitacao da resolucao vertical do dado sismico e necessario gerar modelos que integrem todas as informacoes disponiveis sobre o reservatorio. A maneira mais efetiva de se integrar o dado sismico no processo de caracterizacao de reservatorios e por meio da geracao de modelos de impedância acustica derivados do processo de inversao sismica. O objetivo deste trabalho e mostrar como a inversao sismica para a impedância acustica pode auxiliar e melhorar o processo de caracterizacao de reservatorios, comparando os resultados obtidos por meio da aplicacao de dois metodos, a inversao recursiva e a inversao sparse-spike. Os metodos de inversao sismica aqui estudados sao aplicados em um modelo sintetico de referencia, que possui a forma de uma cunha, modelo esse que representa de forma realista afinamentos estratigraficos e feicoes como pinchouts, frequentemente encontrados em reservatorios turbiditicos de aguas profundas. Com os resultados obtidos podem ser vistas vantagens em se utilizar o processo de inversao sismica tanto na determinacao da geometria dos corpos que formam o reservatorio, como tambem na obtencao das propriedades petrofisicas, e por consequencia modelos mais precisos sao gerados e as previsoes de comportamento do campo podem ser feitas de uma maneira mais efetiva.

Petrophysical Measurements From Drill Cuttings: An Added Value for the Reservoir Characterization Process

Summary Permeability and porosity are necessary for reservoir characterization, and cuttings can provide quick information using dedicated measurement techniques. In this paper, we present the first applications of these techniques on real reservoir characterization cases and the comparisons with logs and core data. The method of permeability measurement from cuttings is based on a pressure pulse applied to a cell filled initially with cuttings saturated with viscous fluid in the presence of trapped gas. The permeability is derived from the transient response of the oil invasion into the cuttings by using a numerical approximation of a mathematical model. The porosity of dry drill cuttings is measured using the routine helium technique. These methods were tested and validated by using various samples of crushed rock of known permeability and porosity. Both measurement techniques are fast, require light conditioning, are applicable over a large range of permeability, and need only 1 mL of sieved rock to be carried out. In this paper, we present a field application of an integrated drill cuttings measurement program [permeability, porosity, nuclear magnetic resonance (NMR) T2 distribution] on a carbonate reservoir. Various drilling conditions [including water-based mud (WBM) and oil-based mud (OBM)] and lithologies have been investigated to develop the different techniques that are presented in the paper. The question of whether measurements on cuttings are representative of the native reservoir is of primary importance and was checked by comparing the consistency of the porosity measurements obtained from cuttings with other data (cores or logs). The overall results demonstrate the added value of k and ϕ measurements from cuttings in addition to the data that are commonly collected.

Integration of seismic methods with reservoir simulation, Pikes Peak heavy-oil field, Saskatchewan

Reservoir characterization is essential for providing optimal recovery from heavy-oil fields. The process of reservoir characterization is demonstrated for a steam injection project at Pikes Peak heavy oil field near Lloydminster, Saskatchewan, Canada. Geologic, geophysical and reservoir engineering data are used to improve the interpretation of reservoir conditions. There is ambiguity in modeling any of these data. However, in modeling all data sets in “cooperative inversion,” ambiguity is decreased, thereby enhancing our knowledge of the reservoir. One of the main benefits of this oil-field modeling is that bypassed oil and steam fronts are effectively mapped.

Finite-Element/Rapid-Response Approach Promotes Collaboration

Technological advancement, particularly in exploration and development efforts, has often left unfulfilled the promise of geoscience and engineering working together more collaboratively and efficiently. But a new approach that combines finite-element (FE) technology with a “rapid response” approach to reservoir modeling is encouraging geoscientists and engineers to shift workflow dynamics from autonomy to collaboration. The new technology, which employs true unstructured 3D mesh, allows modeling time to be reduced from months to weeks, broadening the application to reservoirs once considered impractical. Rapid-response reservoir modeling (similar to top down) starts with the simplest model to obtain all pertinent reservoir information: boundaries, volume, skin, drive mechanism, porosity, permeability, flow barriers, etc. These models are built by employing Resolve, a software package that synchronizes all traditional analyses: material balance, trend analysis, pressure-transient analysis, and simulation. The tool honors full fluid-flow physics, achieves extreme precision when necessary, and iterates rapidly to allow testing of all reasonable scenarios. Houston-based Object Reservoir has used the technology in association with more than 50 companies. Conventional reservoir simulators, originally developed in the 1960s, use finite-difference (FD) approaches for solving fluid-flow equations. FE methods have been developing for nearly 65 years and already have been applied in diverse industries including automotive, aerospace, manufacturing, and construction. Until recently, FE methods were not applied in the oil and gas industry. Some early attempts failed because of a lack of theoretical foundation for handling the nature of fluid flow. In the late 1970s, pioneering work by a variety of researchers led to FE formulations that were stable and accurate for fluid flow. FE methods are easily contrasted with FD, which can be thought of as a collection of gridblocks with distinct properties and step changes at each boundary. The FE method uses spatial integration mathematics with hexagonal or tetrahedral elements. Over each element, a linear variation of the pressure and saturation solution is assumed. This produces a smooth transition of reservoir properties within elements and across boundaries. Then, the equations for governing the flow of oil, gas, and water hold on average over each element, thus conserving mass. The result is a system of equations for values of pressure and saturation at the vertices of the elements (as opposed to gridblock averages in FD methods) that can be solved using standard well-established procedures. FE methods allow for a richer and more mathematically rigorous representation of flow characteristics. FE methods enable advanced computational capabilities naturally. The unstructured grids are useful for boundary-conforming and adaptive meshing, elimination of grid-oriented effects, and advanced visualization. The oil and gas industry is beginning to embrace this technology because of its flexibility, accuracy, ease of use, and workflow/productivity efficiency. Equally as important as the technology is the process employed to use it. The Dynamic Reservoir Characterization process is collaborative in nature. It facilitates communication and interaction between geoscientists and engineers through all phases of the asset life cycle. Enabled by the technology, the process reconciles reservoir-characterization differences between geoscientists and engineers and unites asset teams around all of their knowledge, yielding a common decision-making platform. Traditional modeling workflows are often best characterized by one-way data transfers from the geologist/geophysicist side to the engineering side. However, a highly collaborative, multidisciplinary process uses a “continuous improvement loop” to converge on the solution.

Combining Gradual Deformation and Upscaling Techniques for Direct Conditioning of Fine-Scale Reservoir Models to Interference Test Data

Summary Reconciling multiscale data for reservoir characterization is a crucial issue, because different data types provide different information about the reservoir architecture and heterogeneity. It is essential that reservoir models preserve small-scale property variations observed in well logs and core measurements and capture the large-scale structure and continuity observed in global measures such as well-test and production data. In this paper, we present a new methodology to directly update fine-scale geostatistically-based reservoir models by combining gradual deformation parameterization for the fine-scale geostatistical model, and an upscaling technique for the coarse-scale flow simulation model. As consequence, both fine- and coarse-scale models are updated by dynamic data during the history matching process. The proposed methodology includes: Perturbation of the fine-scale geostatistical model using the gradual deformation parameterization. Gradual deformation ensures the preservation of the overall geostatistical properties of the fine model. Generation of the coarse-scale flow simulation model by upscaling the fine-scale geostatistical model. Fluid-flow simulation and sensitivity computation of the flow simulation results with respect to the fine-scale parameterization. This sensitivity computation is analytical and takes into account the upscaling process. Direct updating of the fine-scale geostatistical model using classical optimization process. Direct updating ensures consistency between the fine- and coarse-scale models. The accuracy of the proposed methodology was improved by calibrating the flow simulation model. The objective of this calibration is to reduce the error introduced by the upscaling step during the flow simulation. We applied successfully our methodology for fine-scale reservoir characterization process by integrating permanent downhole gauge measurements directly into a 3D-geostatistical model containing about two million gridblocks. This test is designed to highlight several key issues of the proposed methodology: Efficiency of the upscaling step, coupled with gradient-based optimization to speed up history matching. Usefulness of the calibration step for a correct integration of upscaling techniques in history matching. Capability of the methodology for maintaining consistency and coherency between fine-scale and coarse-scale models. Improvement of the reservoir characterization process by integrating dynamic data at both fine geostatistical scale and coarse simulation scale.

Trace shape and multi-attribute seismic facies analysis applied to paleocene/eocene reservoirs on deepwater Campos Basin

This paper illustrates a new reservoir characterization approach using seismic pattern recognition methodology based on principal component analysis, trace shape and 3D multi-attributes classification on a set of 3D seismic data volumes. We develop the reservoir interpretation workflow (figure 1) as follows: 1) Seismic facies maps obtained by Kohonen's Self Organizing Map (SOM) Neural Network method to seismic facies volume from a set of various seismic attributes, obtained by Hierarchical classification method; and 2) Statistical analysis of available seismic attributes by application of Principal Component Analysis (PCA) statistical method before classification. How to discriminate the amount of information that each geophysicist is dealing with, in a reservoir characterization process and what is the suitable procedure to help to discriminate between data and information? We present some results of its application on the Paleocene/Eocene reservoirs of a Campos Basin field.

A Potential Approach to Predict Wax Precipitation from Reservoir Core Analysis

In the context of reducing production costs for the oil industry, this paper aims to suggest a way for predicting wax precipitation at an early stage of the reservoir characterization and production process. In this respect, reservoir core extracts and production oil-saturated fractions have been herein analyzed by high temperature gas chromatography (HTGC) in order to quantify the high molecular weight hydrocarbons (HMWHC) which are at the origin of wax deposits in the tubing and surface facilities. Samples of oils and associated reservoir cores from two adjacent but non-communicating fields are considered in this paper. Wax deposition is documented for Field P but not for Field A. It is demonstrated that the reservoir core extract of Field P is substantially enriched in HMWHC when compared to the produced oil, whereas for Field A, with no production problems, both profiles (oil and reservoir core extracts) are similar and depleted in HMWHC. These results suggest that fields exhibiting a risk of wax precipitation could be identified during the exploration phase as soon as reservoir cores are available. Moreover, it can be envisioned that such additional data provided by the saturates distribution can potentially be used in future thermodynamic models (derived from those currently applied for assessing wax precipitation in pipelines during the transport of produced oil) in order to quantitatively predict, at an early stage of reservoir characterization, paraffins precipitation in reservoirs and tubings during production. The preliminary computed results obtained for the produced oil and the reservoir rock extract of Field P indicate that the temperature of paraffin crystallization onset is significantly under-estimated when using the composition of tank oil (42°C)-heavy paraffins are already deposited. On the other hand, the predictive calculation, using the core extract (52°C) and which can be performed as soon as a core sample is available, will allow us to minimize the risk of paraffin deposition during production and transportation. Corresponding author (I. Kowalewski)

Application of Geostatistics for Reservoir Characterization-Accomplishments and Challenges

Geostatistics has been used to improve the reservoir characterization process for the last fifteen years. This article briefly discusses the accomplishments so far, and discusses the future challenges. What Is a Reservoir Characterization Process? Reservoir characterization is a process of integrating various qualities and quantities of data in a consistent manner to describe reservoir properties of interest at inter well locations. Appropriate weight should be given to the quality and the scale of the data, and data should be integrated such that we can predict the future performance of the reservoir. Our goal in reservoir characterization is not to seek the truth about reservoir; instead, to build a reasonable reservoir model which is adequate to predict the future performance. The model will not only be dependent on the type of data available, but it should also be dependent on the type of flow process we are trying to simulate. More complex the flow process (e.g., CO2 process), more detailed will be the reservoir description; more simple the flow process (e.g., dry gas reservoir), simpler will be the reservoir description. Reservoir description process is not new; since the first oil discovery, oil companies have used all the available data techniques to describe the reservoir so that the next well to be drilled will be based on more information than a prior well. However, several changes have taken place in the last fifteen years. Some of these changes are listed below:We have better and faster computers so that we can handle more complex algorithms, and can generate detailed reservoir descriptions in a reasonable amount of time. PC revolution has brought the computer power to small players, making it feasible for even small operators to harness the power of detailed reservoir description processes.Several new algorithms have been developed in the last fifteen years which allow integration of various types of data in an easier fashion.As the reservoirs get more mature, there is more need to describe the reservoir in more details so as to locate the remaining hydrocarbons.There is an increasing recognition that representation of heterogeneities is as important as representing correct physics in the flow simulators. What Is Geostatistics? Geostatistics is based on a simple principle that geological data are spatially correlated. This spatial correlation is quantified and is utlilized to determine the weights assigned to the nearby samples to estimate the value at the unsampled location. Geostatistics has been used in mining industry for several years. Its use in petroleum industry is of relatively recent origin. To address the unique problems encountered in petroleum engineering, several new geostastical techniques have been established in the past several years. Some of these techniques are discussed below. Accomplishments to Date Several papers have been published in the literature to demonstrate the application of geostatistics. It will be impossible to list all the successes of various geostatistical techniques. Instead, an effort is made to highlight the accomplishments which are widely used and embraced by oil companies.

Improving Asset Performance Through Application of a Structured Decision Process

This paper (SPE 60852) was revised for publication from paper 56579, originally presented at the 1999 SPE Annual Technical Conference and Exhibition held in Houston, 3–6 October. Original manuscript received 17 June 1999. This paper has not been peer reviewed. Summary Company experience, external benchmarking, and application of best practices all contribute to improved capital efficiency and reduced cycle time. Combining these practices with a value-driven decision structure yields a powerful method to advance a business opportunity from inception through completion. Many upstream petroleum companies are using, or developing, this type of method to improve reservoir characterization and development practices. Through direct experience in a variety of operational situations in the Gulf of Mexico, a five-step generic decision model evolved that is straightforward, intuitive, and scalable. The initial definitions of the opportunity, assessment of value, decision-makers, deliverables, and assignment of accountability to advance the opportunity to the next decision point are core to the project. The result is a customized road map from opportunity identification to post-implementation evaluation of results. Any business-process change within an active production operation is likely to meet organizational resistance. Unlike previous initiatives, however, this process has been well-received, primarily because it establishes a usable plan developed by the individuals directly responsible for advancing the business opportunity. We have been directly involved in a variety of applications, including complicated infrastructure retrofit projects, pipeline riser repairs, owner- and non owner-operated development projects, well planning, and operation-support activities. The majority of applications are tangible, real-world situations that all operators routinely face. Each application contributed to the evolution of the model. Lessons learned are presented, including cases that illustrate and reinforce essential principles of the process. Conclusions, in the form of quantified financial and technical results, are also presented. Background During the 1990's, a number of processes and practices to improve asset-management and decision-making performance were developed or applied in the petroleum industry (e.g., decision and risk analysis, value engineering).Within Conoco Inc., initial efforts to improve asset-management performance generated detailed process maps for E&P assets. To improve performance in reservoir characterization, a full-asset life-cycle map was developed that covers the geoscience, reservoir engineering, and management-approval steps from acquisition through production and disposal. A companywide education program was used to familiarize personnel on best practices and the reservoir characterization process. Subsequently, this map was expanded to include additional steps covering project-development and operations functions. Additional practices, processes, and principles derived from participation in external-benchmarking, industry, and internal experiences were combined with the more-inclusive process map under and effort named for one of the principles, front-end loading (FEL). Numerous attempts to apply the complex process to improve asset performance were met with limited success and revealed flaws in a complex, fixed process. First, each application had unique attributes and constraints that required departure from or modification to the standard work process. Additionally, workshops and techniques to apply the process were time-consuming and often did not produce near-term improvements that demonstrated the benefit of following a process. Resistance to applying the process was encountered for numerous reasons, including limited time to learn, adapt, and apply a new process; lack of confidence in a process that could not accommodate the unique aspects confronting the asset team; and concerns about stifling creativity. The move toward a simplified process began in late 1997 and early 1998. The process now being used evolved largely through a focused effort to apply a simplified process with two asset teams in Conoco's Gulf Region business unit(GRBU). Focusing the effort on application in one location accelerated the rate at which the simplified process evolved and allowed tailoring of the process and methods to ones that would be accepted and used. The GRBU application pilot could then be taken and used elsewhere in the organization through the central process group (FEL organization). Process Description The basic tenet for the generic process is that all projects follow a distinct sequence (Fig. 1). The initial phase is identification of a business opportunity. The boundaries of the opportunity, high-level assessment of how value could be realized, and assessment of whether the opportunity merits resources to pursue are the main elements of this initial phase.Table 1 gives the phases that follow this initial phase in generic and asset-management terms. Between each phase is a key decision or decision gate. At each decision, the opportunity can be approved to proceed to the next phase, shelved, postponed, or recycled for additional work. Several important principles apply at the decision gates.

The Impact of Integrating Static and Dynamic Data in Quantifying Uncertainties in the Future Prediction of Multiphase Systems

Summary This work presents a qualitative analysis of the uncertainties in performance prediction for a reservoir characterization process in which static and dynamic data are combined. Using primary, single-phase production data as the dynamic constraint in the inversion, we evaluate the quality of the models when they are used in alternative or subsequent production scenarios. We conclude that, provided the well configuration remains the same as that used for the dynamic constraint in the inversion, the models perform well when the production stage remains single-phase, primary depletion, even at the individual well level and for future prediction. For multiphase primary production, there is also a reasonable match in performance, although not as good as for a single-phase case. This is because such depletion processes are controlled by the permeability in the near-wellbore region, which is adequately reconstituted by the characterization process used; we observed, however, that the multiphase density variations with time had little impact. However, the fine scale, inter-well permeability patterns of the different realizations obtained by the integration of the dynamic and static data are not sufficiently resolved and so are unable to capture adequately the inter-well permeability heterogeneity patterns that are necessary for accurate waterflood performance matching. Thus, the models produced by inversion in which primary recovery data are used as a constraint are inadequate in predicting the performance of processes involving injection.

Reservoir characterization from seismic attributes: An example from the Peciko Field (Indonesia)

In reservoir characterization, 3-D seismic attributes constitute important information which complements well data. The high data sampling provided by 3-D seismic often enables a better description of reservoir heterogeneities and a more realistic assessment of hydrocarbons in place. But the introduction of seismic attributes into the reservoir characterization process should be done with care. It requires a good understanding of the geological model and of the variations of the seismic response due to varying reservoir properties. We will detail this approach in an example from the Peciko field.

Integrated Reservoir Characterization Process Model: a planning and scheduling tool for E&P organization

The ultimate goal of an Exploration and Production (E&P) organization is to increase reserves and optimize production in a cost-effective manner within the current Health, Safety and Environment regulations. Efficient reservoir management requires in-depth knowledge of reservoir properties and their distribution within the field. Saudi Aramco's Exploration Organization formed a multidisciplinary team in order to develop an Integrated Reservoir Characterization Process Model (IRCPM).

Pavayacu Field, Peru - A Case History for Production Improvement through Reservoir Characterization: ABSTRACT

The Pavayacu field in the Mara[acute n]on basin of Peru is a mature oil field with a declining production rate. The field was under consideration for disposal when a 3-D seismic survey and reservoir characterization were conducted. These studies led to a refined understanding of the hydrocarbon distribution, which led to a 10 fold increase in daily production and additional recoverable reserves. The main reservoir in the Pavayacu field is within fluvial deltaic sands of the Vivian formation. The overall trapping mechanism is controlled by asymmetric anticlinal folding of the reservoir over basement faults. Hydrocarbon distribution and production is greatly influenced by smaller scale reservoir heterogeneities within a seemingly homogenous sand. Small scale reservoir heterogeneities were successfully resolved through an integrated reservoir characterization process where hydrocarbon pore volumes (HPV) were found to be related to seismic amplitudes derived from the 3-D seismic survey. Additional well locations were successfully selected not only based on the 3-D structural data but also on the HPV distribution. Six wells were drilled based on these analysis resulting in individual flow tests in excess of 4000 BOPD. The one well location based only on the 3-D seismic was not successful. As a result of this studymore » overall field production was increased by an order of magnitude and the field is no longer a candidate for disposal.« less

Effects of a Partially Communicating Fault in a Composite Reservoir on Transient Pressure Testing

Summary Many reservoirs are faulted, and hydraulic characterization of these faults is essential for the design of field-scale developments. In addition to the effect that a fault has on fluid flow in the reservoir, it may separate two different reservoir regions with distinctly different properties. The detection of the properties on both sides of the fault and the distance to the fault are important in the reservoir-characterization process. In this study, a linear fault is modeled as an infinitesimal-thickness skin boundary. Analytical solutions for pressure-transient behavior for a line-source, constant-rate well in a composite reservoir are obtained with one Fourier space transformation and time-space Laplace transformations. The solutions are presented for strip and infinite reservoirs. This study examines drawdown-pressure and pressure-derivative behavior and extends and generalizes many studies presented in the past. Correlating parameters for pressure-transient responses are presented. The possibilities of boundary detections are considered, and interference pressure responses in a composite, strip reservoir are briefly discussed.