Understanding reservoir architecture is critically important to effective reservoir management. Misinterpreting reservoir compartmentalization, for instance, can result in non-optimal well placement, completion strategy, and facilities design as well as large errors in reserves, drainage volume and production rate predictions. Downhole fluid analysis along with complementary techniques including geochemical, mud-gas and pressure analyses provide valuable insights into reservoir architecture. Each analytic method relies on different fluid traits and has its own limitations. With systematic integration of different methods, the synergy delivers a more accurate characterization of the reservoir.
In this paper, we link traditional and novel fluid analysis methods to build a more complete interpretation of the reservoir fluids and provide greater insight into reservoir architecture. This leads to improved understanding of structural history, hydrocarbon migration and entrapment, reservoir connectivity, and fluid contact levels. This, in turn, enables better well placement and more effective development planning. We highlight three case studies in which we have successfully combined various fluid-based techniques for improved reservoir characterization.
Introduction
Determining connectivity at the reservoir scale remains the elusive goal for predicting long-term production profiles. Characterization of reservoir architecture and the fluids therein is the biggest challenge in achieving this goal. In addition to 3D seismic imaging, drill stem testing and extended well tests were traditionally the only available methods for detecting compartmentalization and flow boundaries. However, in deepwater or similar settings, full-scale testing is inordinately expensive and environmentally taxing. Moreover, interpretation of well test responses in turbidite and on lapping channel reservoirs can be highly non-unique due to the complex architecture of such reservoirs. Today, novel techniques such as Downhole Fluid Analysis (DFA), mud-gas analysis and geochemical fingerprinting can be integrated with geologic data to better assess reservoir continuity and/or compartmentalization before field development commences. From these fluid property data and geologic models, dynamic reservoir models can be built to accurately simulate production and help select optimal reservoir management policies.
This paper includes examples in which we integrate pressure gradient, PVT, mud-gas, geochemical and downhole fluid analyses with available geological and geophysical data for the identification of flow barriers, evaluation of connectivity across faults and prediction of fluid contacts.
Downhole Fluid Analysis
In recent years, formation sampling and testing tools have seen the introduction of an array of downhole fluid property measurements. These include optical absorption spectroscopy, optical reflectance, fluorescence and a few other non-optical measurements. The spectroscopic DFA technique utilizes optical absorption properties of reservoir fluid in the visible to near-infrared (NIR) range. Optical spectra are obtained in real time and at in situ conditions, and fluid composition is derived from the signature using the proportion of methane (C1), ethane to propane (C2–5), the hexane plus fraction (C6+), and carbon dioxide (CO2). The gas-oil-ratio (GOR) of the fluid is then estimated from the derived composition (Mullins et al, 2005a, Dong et al, 2006, Fujisawa et al, 2006). Additionally, the differences in absorption spectra between reservoir fluid and oil-base mud (OBM) or water-base mud (WBM) are used to estimate fluid sample contamination with the drilling fluid. The downhole fluorescence measurement is used to identify fluid phases. This is especially useful for near critical fluids. Fluorescence is also sensitive to liquid dropout in a condensate gas when the flowing pressure falls below the dew point and can therefore be used to monitor fluid phase separation in real time to ensure representative single-phase gas samples are collected.
