CIVILICA We Respect the Science
(ناشر تخصصی کنفرانسهای کشور / شماره مجوز انتشارات از وزارت فرهنگ و ارشاد اسلامی: ۸۹۷۱)

Geological Reservoir Modeling of Ilam Fm in the Sirri D Oil Field Based on Deterministic and Stochastic Approaches

عنوان مقاله: Geological Reservoir Modeling of Ilam Fm in the Sirri D Oil Field Based on Deterministic and Stochastic Approaches
شناسه ملی مقاله: IPEC02_111
منتشر شده در دومین کنگره مهندسی نفت ایران در سال 1386
مشخصات نویسندگان مقاله:

Seyed Abolfazl Miri - Graduated Student of Petroleum Exploration, Petroleum Faculty of Tehran, Petroleum University of Technology, Tehran, Iran
Mahmood Afshar - Professor of Petroleum Faculty of Tehran, Petroleum University of Technology, Tehran, Iran
Alireza Bashari - Professor of Tehran University, Tehran, Iran

خلاصه مقاله:
Developing accurate reservoir geological model is essentially important for reservoir characterization. A properly constructed reservoir model can be used to quantify hydrocarbon in place and to optimize hydrocarbon production. The characterization of reservoir is typically achieved by integration of all available data (from geology, petrophysics, seismic and production). An Iranian offshore carbonate reservoir is presented in this paper. The well log interpretation results of 22 wells are used for porosity modeling over the Ilam Interval. In this study, the Ilam Formation is divided into 5 depositional zones and a structural reservoir grid of 214500 cells is generated.In this paper, seismic attributes such as instantaneous phase, are integrated with well data for porosity molding. The spatial directional variogram analysis is done for each zone separately. The deterministic algorithms, kriging and collocated co-kriging, as well as the stochastic methods, Sequential Gaussian Simulation (SGS) and also SGS with a seismic trend as a secondary variable, are used and their results are compared in this work. The seismic attributes showed a correlation coefficient of 40 % with porosity for the zone 5 in the wells, so the modeling is focused on this zone. When a seismic trend was used as a secondary variable, the SGS and kriging algorithms generally yielded better results, however, the seismic trends were misleading for some regions.

کلمات کلیدی:
Reservoir Modeling, Structural Modeling, Property Modeling, Sirri D, Ilam Formation, Seismic Attributes, Variogram

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/147037/