The Upper Assam basin is a major onshore sedimentary basin located in the Assam-Arakan geological province in the north-eastern part of India. This case history of a high permeability, stratified sandstone reservoir of the Lower Eocene formation in Upper Assam basin illustrates how integrated pressure transient analysis coupled with geological, geophysical, petrophysical and production information can be used for construction of dynamic fluid flow models to provide better reservoir description for reservoir simulation study. Chronostratigraphic and litho-stratigraphic layering of reservoir units for this field done earlier through seismic and log interpretation suggested isolated units. Such a model led to the computation of high primary recovery factors. Independent analysis of well tests was found to yield conflicting results, especially with respect to outer boundary configuration. The reservoirs comprising of fine to medium grained sandstones with interbedded shale/carbonaceous shale are located at around 3600 m depth, generally very thin (1–5 m) and exhibit rapid lateral variation making well-to-well log correlation unreliable in many instances. Consistent modeling of flow barriers through analysis of all available well tests and integration of the same with other geo-scientific data led to a more reliable and consistent interpretation of field observations and facilitated refinement of reservoir description. A 3D-3P reservoir simulation study carried out with this model facilitated in establishing the fact that several sand units/reservoirs in the field under study are in pressure communication with a common aquifer system. This information allowed more reliable estimates of in-place reserves and provided good data for fine-tuning the reservoir model to arrive at reasonable history match. The new model used in reservoir simulation is much more plausible and brings out the importance of using dynamic information for reservoir characterization. Performance prediction of the field based on the new model aided in making realistic assessment of future production profiles and proper planning for field installation of formation water disposal and artificial lift facilities. Introduction Reservoir characterization is the process of defining reservoir properties and geological conditions for evaluating reservoir performance and forecasting future behavior. Between the micro and mega scales of reservoir heterogeneity, it is important to describe and analyze those reservoir characterization parameters that impact fluid flow. This leads to an economically optimized and contextually correct reservoir-engineering program. The ultimate goal of most reservoir engineering programs is to develop a mathematical model that closely reproduces known reservoir behavior. Such a model can be used as a forecasting and reservoir management tool. These models use large scale averaging to define grid block properties. Well testing is one of the most important means of measuring the properties of a reservoir at such a scale. In recent years, well testing has undergone significant technological changes to evolve from a technique for evaluating permeability and skin to diagnosing reservoir flow models1–2 and assisting reservoir management3. The Dikom oilfield is an example of a geologically complex field. Crude oil production is obtained from about 3500 m [11500 ft] deep, over-pressured reservoirs located in multiple, stacked, relatively thin sands of about 2 to 5 m [7 ft to 16 ft] thickness. Formation permeability varies from as low as 50 md to as high as 6000 md. Thin sands defy reliable sand to sand correlation and identification of reservoir units. Accurate interpretation of sand development pattern is beyond the resolution of seismic data acquisition due to large depths and thin sands. Lithostratigraphic correlation based on well logs is problematic due to very thin sands and extreme heterogeneity. The increased dependence on transient well testing as a tool for reservoir characterization was, therefore, spontaneous.
s) The maferia!. as presented, does not necessarily reflect any pesfflori c? ffieS-xiety of Petroteum Enginaera. ita officers, or membwa Pap= present~at sPE meetings are SUWCC! to puicafion rewew=y Editorial Commiflees OT the Scciew _--. ----Petmfeum Engineers flectmnic reprbducfion, distribution, or storage of any pafl of this paper for commercial purpoaea without the witten conaamt of the Society of Petroleum Engineers is pmhibii Perinission to reprcduce in print is restricM to an abstract of not more than 3430 wmda, illustrations may not be copiad The abatract must contain conspicuous acknowledgment of where and by whom the paper was presented Write Librarian, SPE, P 0 833833, Richardson. TX 7508>3833. U S.A. fax 01-QTZ-952-M3S AbstractInvasion of mud filtrate into jxxmeable formations impedes accurate formation a'aluation and impairs producibility of oil and gas reservoirs. 'The paper descrilxs a ease study to demonstrate the time lapse effect of invasion on wireline log response and its effeet on hydrocarbon producibility.
Evaluation of thin, highly permeable, stratified reservoirs in the Lower-Eocene Formation in Upper Assam, India poses a formidable challenge. The problems include identification of thin beds, ascertaining the type of fluid based on wireline log response. establishing vertical and lateral continuity of the reservoirs and stratified nature of these thin reservoirs. An integrated multidisciplinary approach has been adopted for solving these complex formation evaluation problems. P. 315
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.