Reservoir Characterization Through Well Test Analysis Assists in Reservoir Simulation - A Case Study

Abstract

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.

Case Study of Petrophysical Evaluation Utilizing Well Logs Data with Optimization of Reservoir Cut-off Parameters

“…Quality of well logging data also plays a significant role in determining HC production potential as well logging data are regularly utilized for seismic velocity calibration, wavelet estimation, low-frequency model building, and time-to-depth conversion that yield a high-quality seismic reservoir description [1]. Several studies [2][3][4][5] have concluded that relationships between various petrophysical parameters, reservoir characterization, and production rate analysis minimize reservoir evaluation uncertainty. Evaluation of subsurface formation petrophysical properties using well logs, well test, and core data can be a source of information on many reservoir properties such as lithology, permeability, porosity, clay volume, grain size, fluid saturation, and net pay thickness.…”

Petrophysical evaluation of well log data and rock physics modeling for characterization of Eocene reservoir in Chandmari oil field of Assam-Arakan basin, India

“…Well logging plays a crucial role in the determination of the production potential of a hydrocarbon reservoir (Ellis 1987). Several authors namely, Joshi et al (2004), Neog and Borah (2000), Ishwar and Bhardwaj (2013), have shown the relation of different petrophysical parameters with the reservoir characterization and production, and hence reduced the uncertainty of reservoir evolution in Upper Assam basin. The petrophysical evaluation of log and core data provides main properties such as lithology, porosity, clay volume, grain size, water saturation, permeability and many others, which are essential for the evaluation of the reservoir formation (Rider 1996;Mukerji et al 2001;Sarasty and Stewart 2003).…”