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Collaborating Authors
Fluid modeling, equations of state
Abstract The acquisition of gas in mud data while drilling for geological surveillance and safety is an almost universal practice. This source of data is only rarely used for formation evaluation due to the widely accepted presumption that they are unreliable and unrepresentative. Recent developments in the mud logging industry to improve gas data acquisition and analysis has led to the availability of better quality data. Within a joint ELF/ENI-Agip Division research program, a new interpretation method has been developed following the comprehensive analysis and interpretation of gas data from a wide range of wells covering different types of geological, petroleum and drilling environments. The results, validated by correlation and comparison with other data such as logs, well tests, PVTs etc, enable us to characterise:lithological changes, porosity variations and permeability barriers, Seal depth, thickness and efficiency, Gas diffusion or leakage, gas/oil and hydrocarbon/water contacts, vertical changes in fluid over a thick mono-layer pay zone, vertical fluid differentiation in multi-layer interval, biodegradation. The comparison between surface gas data, PVT and geochemistry data clearly confirms the consistency between the gas show and the corresponding reservoir fluid composition. The near real time availability, at no extra acquisition cost, of such data has led to:the optimisation of future well operations (logging, testing,.…), a better integration of while drilling data to the well evaluation process, a significant improvement both in early formation evaluation and reservoir studies especially for the following applications where traditional log analysis often remains inconclusive: very low porosity reservoirs, thin beds, dynamic barriers and seal efficiency, low resistivity pay, light hydrocarbons. Examples show both wellsite quicklook with simple lithological and fluid interpretations and more complex reservoir and fluid characterisation applications in varied geographical and geological contexts that demonstrate how GWD data is integrated with more standard data sets. 1. INTRODUCTION The measurement of drilling gas data (gas shows) is standard practice during the drilling of Exploration and Development wells. Continuous gas monitoring sometimes enables us to indicate, in general terms, the presence of hydrocarbon bearing intervals but rarely to define the fluid types (oil, condensate and/or gas, water). Gas data are at present largely under-utilised because they are considered unreliable and not fully representative of the formation fluids. There are many reasons for this. On the one hand, poorly established correlations between reservoir fluids and shows at surface. On the other hand, the influence on recorded data of numerous parameters such as formation pressure, mud weight and type, gas trap position in the shaker ditch, mud out temperatures, etc. One reason may be the very low cost of such data, often equated with low value. Until a few years ago, the analysis performed on gas shows was generally restricted to the use of Pixler and/or Geoservices diagrams (or equivalent), Wetness, Balance, Character and Gas Normalisation (Pixler, 1968 Haworth et al., 1985; Whittaker & Selens, 1987; Wright, 1996).
- Geology > Rock Type (1.00)
- Geology > Geological Subdiscipline > Geochemistry (0.67)
Hydrocarbon Field Planning Tool for medium to long term production forecasting from oil and gas fields using integrated subsurface - surface models
Beliakova, N. (Shell International Exploration and Production) | van Berkel, J.T. (Shell International Exploration and Production) | Kulawski, G.J. (Shell International Exploration and Production) | Schulte, A.M. (Shell International Exploration and Production) | Weisenborn, A.J. (Shell International Exploration and Production)
Abstract The Hydrocarbon Field Planning Tool (HFPT), recently developed by Shell, provides capabilities for rigorous integrated subsurface-surface production forecasting in the medium to long term (1–30 years). HFPT can be used for gas, gas-condensate, oil and mixed gas-oil fields. HFPT models allow business optimisation by making more efficient use of the existing assets and by reducing investment costs in the new fields. In the simulation, HFPT uses a pressure-balanced solution of the integrated system: from the reservoir(s), through wells and surface facilities, to the delivery point. A wide range of fluid models is available, from simple gas-condensate and black oil PVT models to multi-component models with EOS flash calculations. HFPT provides optimisation functionality for maximising the returns in oil and gas fields, while accommodating operational preferences for production allocation and network constraints. It can also model injection networks and optimal lift gas distribution. Introduction The need for an integrated approach to dynamic field modelling has now been accepted by many players in the oil industry [1]. Issues which can be analysed in an integrated model, and which cannot be adequately addressed in a stand-alone reservoir model (or multiple stand-alone models), include:Pressure interaction between surface and subsurface. Pressure interference between different reservoirs and wells connected to a shared surface facility. An example is a high-pressure well backing out a low-pressure well. Mixing of dissimilar fluids from different reservoirs in the production network. Influence of facility constraints, e.g. separator limits, on a set of reservoirs connected to a shared facility. Production optimisation in the overall system against a set of common criteria. A number of field studies, performed using integrated subsurface-surface models, have already been reported, e.g. [2][3], showing benefits of such models. Over the past ten years, a wide range of applications from commercial vendors have appeared on the market which allow modelling of the subsurface and surface in an integrated way. Most of the available tools are designed either for a very simple reservoir description or for a simple surface description, or both. Hydrocarbon Planning Tool (HFPT) has been developed by Shell to fulfil the need for rigorous integrated subsurface-surface production modelling. It has been designed for accurate medium to long term forecasting, for optimising of production from existing fields, for analysing near-field potential in mature fields and for developing new fields. Currently, HFPT focuses mainly on medium to long term forecasting which is dominated by subsurface behaviour. However, surface and process facilities models can also be modelled in great detail, when needed. Requirements for Integrated modeling An integrated subsurface-surface model consists of the following main data modules, illustrated in Figure 1:PVT model. Subsurface model. Surface production system model. Processing facilities model. Overall integration and control, contracts, optimisation targets, development planning.
- Europe > United Kingdom > North Sea > Central North Sea (1.00)
- Asia (1.00)
- Oceania > Australia (0.69)
- Europe > United Kingdom > North Sea > Central North Sea > Central Graben > Block 23/26 > Eastern Trough Area Project (0.99)
- Europe > United Kingdom > North Sea > Central North Sea > Central Graben > Block 23/16 > Eastern Trough Area Project (0.99)
- Europe > United Kingdom > North Sea > Central North Sea > Central Graben > Block 22/25 > Eastern Trough Area Project (0.99)
- (9 more...)
- Reservoir Description and Dynamics > Reservoir Simulation (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management (1.00)
- Reservoir Description and Dynamics > Fluid Characterization > Fluid modeling, equations of state (1.00)
- Facilities Design, Construction and Operation > Processing Systems and Design (1.00)
Abstract Adequate modeling of a hydrocarbon production system may require integration of several reservoir models with a model for the surface network and a model for the processing facilities. The degree of detail in each model should be in accordance with its impact on the business case. Compositional modeling of the hydrocarbon streams is usually highly desirable for volatile oils, gas-condensates and production systems in which different streams are mixed. However, compositional modeling is notoriously involved and CPU-intensive. Hence it has so far only been applied in an approximate way, with a few lumped components and reduced detail in the geological reservoir model(s). These approximations will often defeat the purpose for which compositional modeling was brought in. Compositional modeling has been implemented in Shell's proprietary Hydrocarbon Field Planning Tool to enable adequate modeling of gas-condensate and volatile oil systems. Surface network modeling was accomplished by interfacing with the compositional mode of the commercial network solver Pipephase. The compositional well streams were generated by extension of Shell's multi-purpose reservoir simulator MoReS with a delumping scheme. This scheme is in essence postprocessing of the well streams calculated on the basis of a two-component reservoir fluid representation. It requires a marginal amount of CPU time, independent of the number of components. In all applications so far the delumping scheme was found to be unexpectedly accurate: the mass rates of the 20-odd well stream components were reproduced with an average relative accuracy of about 0.5 %. The well streams consist of all components mentioned explicitly in the PVT report(s) and typically about 10 pseudo-components to represent the heavy fraction. In this paper the physical considerations are described, which underly the delumping scheme. Also provided are a detailed validation study and the key results of field studies of gas-condensate fields in Australia's North-West Shelf area and in the North Sea. Introduction There is significant commercial benefit in being able to forecast the compositions of well streams and of gas and condensate c.q. crude oil at the sales point. The following examples may serve as illustration.The value of gas recycling is determined by the heavy ends. This recovery depends on the injection gas composition and the component exchange rate. The latter is also influenced by the gas recycling rate. The sales gas composition may be kept within the contractual compositional/contaminant specifications for export gas export or liquefaction feedstock by judicious phasing and blending of production from several fields. The phasing to meet contractual specifications may involve optimisation of installation and/or upgrading of compression. Alternatively, the phasing may involve deferment of e.g. LPG, if a market will become available at a later stage. The design and long term operation of processing facilities may be optimised in advance to minimise bottle necks and to honour the contracts at minimum costs. The oil and gas industry is kept from using full compositional modeling of hydrocarbon production by the dilemma of developing an adequate compositional model for the reservoir fluids and the usually prohibitive computational requirements for using a truly adequate fluid model in geologically realistic reservoir models.
- Oceania > Australia > Western Australia > North West Shelf (0.24)
- Europe > United Kingdom > North Sea (0.24)
- Europe > Norway > North Sea (0.24)
- (2 more...)
- Reservoir Description and Dynamics > Unconventional and Complex Reservoirs > Gas-condensate reservoirs (1.00)
- Reservoir Description and Dynamics > Reservoir Simulation (1.00)
- Reservoir Description and Dynamics > Fluid Characterization > Fluid modeling, equations of state (1.00)
Abstract A full analysis of the problem of coupling two independent industrial simulators, a reservoir simulator and a steady-state network simulator, has been performed. A classification of the industrial needs has been obtained from the examination of several actual cases studies (fields at development, or production stage, requiring performance optimization through short to long term forecasts). Several coupling configurations and specific requirements, for both reservoir and surface software, have been identified to satisfy the industrial needs. Various commercial solutions have been screened to evaluate the adequacy between the software functional capacities and the identified configurations and requirements. Limitations have been brought to evidence. The paper, issued from the work of a multidisciplinary team, presents the details of each step described briefly here above. Practical solutions for improving coupled solutions, i.e. to go beyond the identified limitations and to reduce the elapsed times of the coupled simulations, are provided. An improved mutual understanding of the needs of each discipline concerned by the integration of reservoir and surface has been experienced as essential for a successful integrated approach of field optimization. It is intended in the paper to contribute to a better communication between the various upstream petroleum skills: reservoir, production, surface and process engineers. Introduction It has been well recognized that coupling surface network and reservoir simulations is a critical technology for field development/optimization studies, particularly in the deep offshore area, or when many wells share the same surface network. Various methods have been proposed to solve in a coupled way the reservoir model and the surface model, for enabling time savings (by avoiding multiple information returns between reservoir and surface engineers), and for an improved reliability of the global solution. Since the pioneer work of Dempsey in 1971, the development of a coupled resolution of reservoir and surface models, firstly for application in gas field development and production optimization, has been extended some years after by Chevron for oil field developments in offshore area. Since then, several other major companies have developed their proprietary integrated reservoir/surface solution, and/or have integrated their proprietary reservoir simulator with a commercial network software. To our knowledge, the only reported experience of a compositional integration is from Litvak. In these integrated solutions, the two programs are merged in a unique one (solution named ‘fully integrated solution’ in what follows) ; such a procedure has also been used by Trick for integrating two commercial software Forgas and Imex. Another integration method, enabled by the emergence of message passing libraries as PVM (Parallel Virtual Machine), is to couple independent programs through an interface. In the coupling development of two commercial simulators, Eclipse as reservoir simulator, with Netopt (Hepguler) or with Forgas (Trick), the interface which controls the software communication has been implemented in the surface simulator, the reservoir simulator being a slave process. The coupling location, retained for linking two independent simulators, is either at the bottom hole (Trick), or at the reservoir level with an Inflow Performance Relationship (IPR) represented in both reservoir and surface models (Hepguler).
- Europe (0.93)
- North America > United States > Texas (0.28)
- Reservoir Description and Dynamics > Reservoir Simulation (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Well performance, inflow performance (1.00)
- Reservoir Description and Dynamics > Fluid Characterization > Fluid modeling, equations of state (1.00)
- (2 more...)