Determination of water saturation (Sw) from conventional resistivity and porosity logs has proved difficult in several gas fields within Bolivia. To address this challenge, a method was developed to determine Sw profiles based on pseudo-capillary pressure curves (Pc) derived from transversal relaxation times (T2 distribution) measured by nuclear magnetic resonance (NMR) logging tools. Some of the Bolivian sand reservoirs, producing gas and condensate with a high gas/oil ratio, are characterized by a lack of resistivity contrast above and below the oil-water contact. This problem is attributed to complex mineralogy, including thin shale laminations within sand bodies of variable petrophysical quality, and mostly to very fresh formation waters that average a salinity of 5000 ppm of total dissolved solids. Also, the lack of lateral extension of each reservoir makes cross-well correlation very difficult. The core hypothesis of this original method is to assume that the relation between capillary pressure and pore throat sizes is similar to that between T2 values and pore-size distribution. A consistent scaling factor is used to derive a pseudo-capillary pressure from an NMR T2 distribution. After the pseudo-pressure is calibrated with capillary pressure measurements from laboratory-derived core data, it is combined with density (difference between the produced hydrocarbon and the formation water) and free-water level (FWL) information to compute Sw along the wellbore trajectory. Even so, in general terms, resistivity-based models are still the most consistent and documented foundation in order to compute water saturation; Examples demonstrate the success of this new standalone method of uncovering unforeseen hydrocarbon in place and obtaining accurate Sw as an alternative to the standard, but dubious or inadequate, resistivity method in Bolivia where cretaceous and carboniferous rocks with intergranular porosity are found within several sedimentary basins. Introduction When the conventional methods for the calculation of the water saturation (Sw) profile in the reservoir are not reliable for different reasons, a viable alternative is the calculation based on capillary pressure (Pc) curves. Using the Pc curve, the water saturation (Sw) in the reservoir can be calculated for any height above the free water level (FWL). By knowing the capillary pressure in a point, Sw can be easily calculated without the need of any standard resistivity model, whenever FWL and the fluid density of hydrocarbon can be determined with certain precision. As the capillary pressure is measured directly from cores or samples taken from the formation, normally it is difficult to find continuous information of Pc that allows creating a calculation throughout the whole formation thickness. In such sense, if it is realistic to acquire the value of Pc indirectly, for example by means of electrical logs, then one could virtually compute a continuous Sw. Some authors, Volokitin1 et al., have studied the option of obtaining a continuous curve of Pc from the T2 distribution of transverse relaxation times of a Nuclear Magnetic Resonance (NMR) tool. In our case, we have experimented with the processing of the data acquired from a CMR* tool that includes an application to calculate a continuous curve of Pseudo-Capillary Pressure (P-Pc) and the Sw, from the T2 distribution of transverse relaxation times, the density difference between water and hydrocarbon enclosed in the reservoir and the FWL. The method is essentially based on that the size of the poral throat has a relation with the size of the pore itself. Then as the capillary pressure, by means of calibration, can be derived from the size of the poral throat and likewise from the T2 time distribution of the CMR, we are subsequently able to get the pore size distribution. In conclusion, from a T2 time distribution curve one can, by means of calibration, obtain a Pseudo-Pc curve so that it is used in the calculation of water saturation Sw with the knowledge of the free water level FWL.
A relatively new technique has been applied for the purpose of providing more accurate Permeability information and identify rocks types with good fluid flow characteristics from wireline logs data. The study for which this technique was applied included wells drilled over the last 30 years up to present. When you have a wide range of logging tools and differences in logs scales or presentations it becomes really difficult to identify the existing facies on a depositional cycle just by following the shape of the log curves. Even when you count with a consistent or homogeneous log set of curves, the task of identifying the different facies is often difficult. The technique used applies the clustering K-Means2 algorithm based on wireline logs characteristics to identify the different Electrofacies. The Electrofacies found were very useful to determine rock types with identifiable fluid flow characteristics. Porosity/Permeabilty relationships were then assigned to the various Electrofacies and used to calculate permeabilties during the log analysis. The method was applied for 79 wells from La Peña Field and for the 9 wells from the Tundy field and proved to be very successful in dealing with a wide heterogeneous range of wireline log types when working on a multiwell field petrophysical analysis. The application of this technique is very simple if we look at the existing pattern recognition software designed to identify facies that include the complicated stochastic algorithms which usually requires the operation of skilled users in order to obtain impressive results. This paper presents a description of the clustering K-Means2 algorithm used for the Electrofacies calculations and also shows the permeabilities results obtained in the petrophysical analysis for each of the Facies. Finally some examples of the petrophysical evaluation and the calculated Electrofacies will also be visualized graphically and discussed here. Introduction The La Peña oilfield was discovered by the Bolivian Gulf Oil Company in the sixties decade (1965) and the structure is about 8 Km. long from north to south and 2 Km wide from east to west. The La peña field has been producing oil for 35 years and the Oil Cummulative Production is 35.5 MMBBLS. from La Peña and Bolivar sandstones. The related but hydraulically isolated Tundy oilfield was discovered in 1992 for the State Bolivian Oil Company Y.P.F.B. and is located to the north of La Peña field. To the present the Oil Cummulative Production is over 2 MMBLS. only from the La Peña sandstone. A total number of 82 wells in the La Peña field and 11 wells in the Tundy field were drilled but only 13 wells are producers, 10 from the La peña sand and 1 from the Bolivar sandstone. The La Peña and Tundy oilfields are located east of Santa Cruz de la Sierra - Boliva and are on the eastern side of the Andes orogenic influence (Fig. 1). The producing horizons mainly belong to the Carboniferous San Telmo (La Peña sandstone) and Escarpment (Bolivar sandstone) formations (Fig 2). This sedimentary deposits are lithologically complex and considered to have been deposited mainly in fluvial environments. Permeability data is not often an available data for each well and in continuous depth intervals. The main objective of this study was to obtain permeability data as accurate as possible to have the most reasonable idea of the flow characteristics around the entire fields to be used later in simulation study.
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.
customersupport@researchsolutions.com
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.