Study of key parameters of reservoir viz, porosity, water saturation, permeability and pore size distribution from well logging data is more complicated in carbonate reservoir due to geological heterogeneities than Clastic reservoir.The Magnolia field is located in GOM blocks GB 783 and 784 and produces from Plio-Pleistocene turbiditic sands that form a complex channel/levee sequence penetrated by 16 boreholes. The primary pays consist of two sands, each about 200 feet thick, separated by a 15 foot shale layer. The pays are divided into an eastern gas prone province and a western oil prone province. A reservoir flow simulation model is planned to optimize production from existing wells and to facilitate future field development. Construction of an accurate model is complicated by MDT pressure measurements which indicated compartmentalization below the resolution of conventional seismic analysis, and by overlap of the seismic attributes derived from producing reservoirs, wet sands, and shales.To mitigate these factors, geostatistical inversion was chosen to produce the rock property inputs for the flow simulation models. This approach allowed development of a rock properties model consistent with core data, log data, and geologic constraints as well as seismic information. It also allowed assessment of uncertainty through the generation of a statistically significant number of internally consistent alternate solutions (realizations). A Markov Chain Monte Carlo method was employed to integrate borehole and geologic information to produce acoustic impedance and lithology volumes which were then used to co-simulate porosity, permeability, p-wave velocity, and water saturation volumes. Multiple realizations of these products were reviewed, uncertainty was assessed, and a rock properties model was selected for conversion to a flow simulation modeling format. The entire process can be rerun relatively quickly to accommodate additional wells and improved seismic data or to match production history.

Accurate knowledge of oil saturation and its distribution is essential for any reservoir being considered for redevelopment or for secondary and tertiary operations. Determination of oil saturation forms the only rational basis for prediction of recoverable oil reserves and it is critical in the selection, design and economic evaluation of an oil-recovery process. As technology advances, more of this oil will come within our reach. However, it is essential that we understand the reservoir involved so that proper, economically viable technology can be applied. Thus, the importance of residual oil saturation (SOR) which in turn is the basis for the estimation of remaining oil-inplace. Five techniques to determine remaining oil saturation are currently used. They are coring, logging, chemical tracers, reservoir engineering studies and pressure transient tests. Normally, two or more of these methods are used together and the data evaluated as a whole since each technique has its own advantages and limitations. When evaluated together, a clear understanding of the total reservoir can be obtained. Conventional logging tools and procedures have been used extensively for many years for determination of reservoir and fluid properties. Although SOR determinations normally require a higher degree of accuracy than is commonly achieved by conventional logging methods, the incentive to use logs for SOR measurements remains high. They are often cheaper and easier to use than is the case for other methods which are currently available for measuring SOR.

This paper covers the essentials of the tools, and practice of basic Russian well logs and Russian log analysis techniques. Emphasis is placed on those tools used in Russia which are significantly different than their counterparts in other major petroleum producing provinces. The BKZ Kapotax is five Russian lateral electrical resistivity logs run at different spacings depending on the reservoir thickness. It is used to calculate true formation resistivity. The technique corrects for mud and borehole effects using response curves modeled for a lateral log. This technique uses different tool spacings, borehole size, mud resistivities, diameter of invasion and the resistivities of the five laterals. This paper presents the BKZ method for predicting the true formation resistivity from this combination of lateral logs. Laterals were the primary resistivity log recorded by Russians before the early 1980's. Now the induction conductivity log is also being used, but not in the BKZ technique for determining Rt. Only lateral devices are used for this determination. By using the BKZ method, quantitative information may be extracted from historically recorded data and allows improved evaluation of reservoirs in previously drilled wells. Introduction Oil and gas wells drilled in Russia are classified as either research wells or production wells. Research wells are drilled by the local geologic institutes known as Geologia and include exploration and delineation wells. Production wells are drilled by local production institutes called Neft, for the purpose of developing and producing delineated fields. Most research wells are evaluated with open hole logs such as spontaneous potential (SP), a combination of lateral and normal resistivities, conductivity, microlog, caliper, gamma ray, gamma-neutron, density and acoustic logs along with cores and well tests. In contrast to the relatively complete data package gathered from research wells, production wells generally are evaluated with an SP in combination with a combination of lateral logs recorded at different electrode spacings. This paper describes the methodologies used for log interpretation using the BKZ method in actual Russian production wells. Software under development or available today will greatly assist the evaluation of these resistivity logs. P. 171^

As production declines in a reservoir, management is confronted with the question: Do we have sufficient hydrocarbons remaining for an improved recovery project to be economically viable? The answer requires a knowledge of the remaining recoverable reserves which are determined from the residual oil saturation (Sor). Hence Sor is essential to calculate the reserves that can be produced by the proposed project. The additional income can then be compared with the required expenditures necessary for its implementation to enable establishing whether the project meets the required profitability criteria. However, a project must not be judged on profitability alone. Its riskiness must also be taken into account. If we have two projects with the same profitability, the one that is less risky is obviously preferred. Riskiness can be defined as a measure of the uncertainty of achieving expected results. Riskiness depends on many factors but one of the most crucial will be the uncertainty in the recoverable reserves which is directly dependent on the uncertainty in the measured Sor. Clearly an assessment of the uncertainty in Sor is very important. Introduction An application of Monte Carlo simulation for estimating uncertainty in remaining oil saturation (ROS) or the residual oil saturation flushed by water (Sorw) derived from a Log-Inject-Log technique is presented. Pulsed Neutron Capture (PNC) logging forms the basis for determining Sor by Log-Inject-Log (LIL) techniques. Data taken from a Middle East reservoir is input into a PC based spreadsheet to illustrate the method. This method is less time consuming and does not have the limitations of the cumbersome analytical approach which requires computing the partial derivatives of all the parameters used for calculating ROS or Sorw. In addition the Monte Carlo simulation enables better characterization of the uncertainty. Monte Carlo simulation can be readily adapted to enable comparing different remaining oil saturations and Sorw measurements techniques. Hence, the method has applications for selecting the best technique for a given set of conditions. Quantifying Uncertainty An uncertainty indicator should provide a measure of the confidence that can be attached to a given value. Probably the simplest approach for expressing uncertainty consists of establishing minimum and maximum possible values which can be seen in Table 1. For example a certain technique may yield a remaining oil saturation of 23.78% PV. The minimum and maximum values are 12.5 and 33.79% PV respectively. Analysis of the uncertainty in the derivation of this value may suggest that the true formation remaining oil saturation lies between 21.94 and 25.62% PV and a mean of 24.25% PV. As the uncertainty increases the spread between the minimum and maximum expected values also increases.

Exploration in the Gulf has progressively moved farther and farther offshore. Initially oil companies concentrated on the shelf and then moved into the deep water and the Miocene trend. The Miocene is a well established trend with a considerable amount of producing acreage. With the acquisition and processing of data farther offshore, attention has switched to a new trend in the Lower Tertiary. The Lower Tertiary sits beneath the Miocene and is older. The Tertiary time period includes Pliocene, Miocene, Eocene and Paleocene. We tend to lump everything below the Miocene into what we call the Lower Tertiary because our Wilcox sands are Paleocene and Eocene in age. Most of the cumulative GOM production has been Miocene in age. This is an emerging play in the deepwater Gulf of Mexico, to date there have been 12 announced discoveries out of 19 wells drilled (Figure 1). This trend data is only for Alaminos Canyon, Keathley Canyon and Walker Ridge. There are additional penetrations along trend to the northeast. There is a contradiction between traditional interpretation and NMR data in the Lower Tertiary. An NMR log (CMR) was run with the aim of identifying the best reservoir intervals of Porosity, Swir, and Permeability. The NMR log has many responses depending on the borehole fluid, free fluid and viscosity. These results will be discussed.Oil bearing interval with Swir higher than SwCMR porosity undercalled in oil-bearing intervalLittle free fluid in oil-bearing intervalCalibration of Klog permeability to core Traditional logs indicate the presence and quantity of oil, but provide no information on its quality. NMR is sensitive to oil viscosity. NMR can be misleading in the presence of viscous oil as the oil signal can overlie the bound fluid volumes, resulting in the incorrect evaluation of the reservoir in an oil base mud system. The NMR must be used with caution in an oil base mud system (OBM).