PRAVAP 2 (Petrobras' strategic project for reservoir characterization) aims mainly technology acquisition and development in reservoir characterization. The project is based on a multidisciplinary approach, and the synergism between operational and research teams. New technologies are put together with others already consolidated. This paper presents some of the developments acquired and how they impact the field development and oil production. Introduction Petrobras has been developing its major offshore turbidite oil fields. Improved techniques for reservoir characterization and reservoir engineering (drilling, completion, and stimulation) are required to reduce risks and optimize investments, commonly high in offshore areas. The challenge for developing offshore deep water oil fields has led to a paradigm changing in the early 70's and 80's technology, mostly centered in closely-spaced vertical and deviated wells. The new scenario requires a reduced number of largely-spaced horizontal or multilateral wells. Additionally, some of the internal heterogeneities of turbidite reservoirs are still poorly understood. Facies are well described from cores, but scarce information is available from inter-well areas. Some characterization techniques are particularly indicated for improvement in well location, as refined maps for the reservoir top, well log resistivity modeling, and 3D reservoir modeling and visualization. Multidisciplinary team approach and integration of well, production, fluid and specially seismic data into an integrated model can improve reservoir characterization. Seismic must be intensively used, but special efforts on seismic processing is needed to eliminate noise and to recover high frequencies. High-resolution stratigraphy The Upper Albian Namorado Sandstone form part of an Upper Cretaceous to Lower Tertiary transgressive succession, which is characterized by onlapping, deepening-upward sedimentation throughout the eastern Brazilian margin. The Namorado turbidite reservoirs from the Albacora oilfield are confined to a NW-SE-oriented, 100-km-long, and 40-km-wide sag, which was established in a deep neritic to upper bathyal setting. These turbidites were probably following a tectonically induced depression in the slope related to the eastward tilting of the Campos Basin and resulting downslope flowage of underlying Aptian evaporites. Namorado Sandstone at Albacora field comprises two turbidite successions. The uppermost (Namorado I) is 0–12m thick, and the lowermost (Namorado II) is 28–107m thick. These two sand-rich successions are separated by a 11–17m thick succession of diamictites (debris flow deposits) and bioturbated calcilutites, marls and shales (background sedimentation). Thin (<3.4m) non-reservoir beds (diamictites, calcilutites, marls, and shales) are commonly interbedded with sandstones of Namorado II, comprising 14% of its total thickness. The turbidite reservoirs are composed mostly of unstratified, fine- to very fine-grained sandstones. Subordinate facies include unstratified, coarse- to medium-grained sandstones, and Tab, Tabc, Tbc, and Tc Bouma beds of fine- to very fine-grained sandstones. The sandy reservoirs are poorly sorted, and composed mainly of quartz, feldspar, and fragments of quartzofeldspathic, high-grade metamorphic rocks. Mud matrix includes 3-30% silt, and 1–6% clay. The average framework composition is Q59F38L03. Accessory components consist mainly of carbonate intraclasts (0–11%), and bioclasts (0-9%). Namorado Sandstone can be subdivided into 12 reservoir units (numbered 1 to 12 from oldest to youngest; Fig. 1), mostly on the basis of (1) thicker, widespread non-reservoir beds (marker beds A to D; Fig. 1), and (2) trends of grain size distribution.
Modern logging tools, including Nuclear Magnetic Resonance (NMR), allow geoscientists to integrate data and use advanced petrophysics techniques. The NMR logs estimate permeability curves based on empirical equations and their response are sensitive to the permeability trends in rock layers of a heterogeneous reservoir. Therefore, it is possible to define flow units based on NMR flow capacity. This process can even be enhanced if there are Production Logging results available. This paper presents a technique applicable to well test interpretation which consists in estimating the permeability of flow units through the integration of NMR, formation tests and production log data. The properties of each flow unit such as thickness, average permeability and effective porosity are estimated from the NMR log. Using these data a multilayer flow model is built, in order to determine a multiplicative factor for the prior defined average permeability from each flow unit honoring the results of DST data. Several simulations are performed by changing the horizontal and vertical permeabilities and skin factor for each flow unit, to obtain compatible results with the well test. This technique is applied in Brazilian carbonates. The cumulative NMR permeability curves shows good agreement with PLT data, which means that the NMR can be used as a predictive flow unit identifier when PLT data are not available. In conclusion, the technique permits the interpreter to test various scenarios in a multilayer model, using different combinations of permeability and skin values for the flow units. This petrophysical model can also be used as an input for the dynamic simulation of the reservoir.
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
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.