The Mangala, Bhagyam and Aishwariya Fields were discovered in early 2004 in the northern Barmer Basin of Rajasthan, in northwestern India. The data acquired in the field wells (including almost two kilometers of core) enabled a precise estimation of field stock tank oil initially in place (STOIIP). This paper summarizes the techniques that allowed the estimate of STOIIP to be more precisely defined and to be revised upward by 12%, a substantial increase when dealing with a billion barrel field (Mangala Field). Initial evaluation of the log data indicated a sequence of clean, quartzose sandstones with porosity greater than 25%. High porosities together with resistivity in the oil column over 5,000ohm-m, suggested that water saturations (Sw) were ~15% or even less. Based on the initial data and conventional techniques, the initial STOIIP estimates were made for the three fields. An extensive core analysis programme was begun in appraisal wells, with the objective of improved definition of the actual reservoir STOIIP's. Two appraisal wells were cored with synthetic oil based mud, and Dean-Stark Sw analyses were done. In addition to routine core analyses and the Dean-Stark Sw data, a sizeable set of other special core analyses is also available. This includes extensive capillary pressure data, laboratory NMR, and core electrical properties measurements. The petrophysical dataset verifies the existence of Sw's that are typically less than 5%PV, and often near 1%PV, in a very high-permeability and high-porosity reservoir containing little clay. The reservoir contains a medium gravity, highly paraffinic oil, and is moderately oil-wet. The various laboratory datasets challenged some of the traditional assumptions concerning the use of Archie constants in such reservoirs for Sw calculations. The upward revision of STOIIP is significant, and can be principally attributed to the more accurate estimation of reservoir fluid saturations. As this work demonstrates that very low Sw values exist in the Barmer Basin, the Mangala, Bhagyam and Aishwariya fields can provide a model for the appropriate economic evaluation of similar reservoirs. The laboratory results challenge some of the traditional thinking about the petrophysical properties of reservoirs such as these. It is indeed possible, that high quality reservoirs can have initial water saturations lower than 5% of pore volume on average, and with some zones less than 1%. Conventional log tools and analysis methods will not reveal these low levels without integration with core data and appropriately designed core analysis programmes. Also, and perhaps more importantly, this work clearly demonstrates the economic worth of extensive laboratory measurements and analyses on high-volume, high-value reservoirs such as those of the Mangala, Bhagyam and Aishwariya Fields. Introduction The Mangala, Bhagyam and Aishwariya Fields ("MBA" Fields) were discovered in January 2004 (Yashwant, et al, 2006) by targeting a series of simple, tilted fault-block traps formed within the rifted, Tertiary Barmer Basin (Figure-1).

In 2004, the Mangala, Aishwariya, and Bhagyam fields were discovered in Rajasthan, India. In these high-permeability paraffinic reservoirs, viscosity is one of the main factors controlling performance. Pressure, volume, and temperature (PVT) data show areal and vertical variations in crude properties. Meter-by-meter geochemical core analyses corroborate vertical variations in oil composition. Continuous wireline measurements of nuclear magnetic resonance (NMR) properties and station NMR properties from wells drilled with both water-based muds (WBM) and synthetic oil-based muds (OBM) were also used to calculate a viscosity profile. This paper correlates results from all techniques and shows how NMR measurements can provide oil viscosity profiles in compositionally complex pools.Black-oil PVT samples typically test several meters of reservoir, while Rajasthan geochemical data are available at meter scale. NMR logs provide continuous data, and calibrated to PVT and geochemistry, they can provide the most detailed picture of in-situ viscosity variations.Results were used to construct a detailed spatial description of the reservoir's in-situ oil viscosity. The NMR data helped to define a zone of biodegraded oil up to ∼25 m thick above the oil-water contact (OWC) and showed thin accumulations of higher-viscosity oil on top of minor shale layers within oil columns. The major conclusion is that detailed in-situ oil viscosity profiles can be developed from conventional wireline T2 measurements.

TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractIn 2004, the Mangala, Aishwariya, and Bhagyam fields were discovered in Rajasthan, India. Oil viscosity is a main factor controlling performance from these high-permeability paraffinic reservoirs. PVT data show areal and vertical variations in crude properties. Meter-by-meter geochemical core data corroborates vertical variations in oil composition. Continuous wireline measurements of nuclear magnetic resonance (NMR) properties and station NMR properties from wells drilled with both waterbased (WBM) and synthetic oil-based muds (OBM) were also used to calculate a viscosity profile. This paper correlates results from all techniques, and shows how NMR measurements can provide oil viscosity profiles in compositionally-complex pools.Black oil PVT samples typically test several meters of reservoir, while Rajasthan geochemical data is available at meter-scale. NMR logs provide continuous data, and calibrated to PVT and geochemistry, can provide the most detailed picture of in situ viscosity variations.Results were used to construct a detailed spatial description of the reservoir's in situ oil viscosity. The NMR data helped define a zone of biodegraded oil up to ~25 meters thick above the oilwater contact (OWC), and showed thin accumulations of higherviscosity oil on top of minor shale layers within oil columns. The major conclusion is that detailed in situ oil viscosity profiles can be developed from conventional wireline T2 measurements.Techniques presented allow quick and accurate calculation of oil viscosity profiles from wireline logs, and can reduce the need for time-consuming detailed geochemical measurements. Results directly impacted the static and dynamic modelling of the Rajasthan fields and proposed waterflood designs (different for each field). Procedures described are generally applicable to reservoirs with similar datasets. Finally, the wealth of data presented allows a detailed examination of the viability of several approaches advocated for estimating in situ oil viscosity from wireline NMR measurements.