Pooria Kianoush; Ghodratollah Mohammadi; Seyed Aliakbar Hosseini; Nasser Keshavazr Faraj Khah; Peyman Afzal
Abstract
In the seismic methods, estimation of the formation pressures is obtained by converting the seismic velocity to the pore pressure, and comparing it with the effective pressure during the well-test program. This work is a new challenge regarding the velocity study domain in an oil field in SW Iran. The ...
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In the seismic methods, estimation of the formation pressures is obtained by converting the seismic velocity to the pore pressure, and comparing it with the effective pressure during the well-test program. This work is a new challenge regarding the velocity study domain in an oil field in SW Iran. The reservoir generally consists of carbonate rocks, and contains no shale interbeds. Here, 23 well information, seismic data interpretation, compressional (Vp), and shear velocity (Vs) models are implemented. The models are determined from the combined geo-statistical methods, and the results obtained are compared with the fractal models. The final Vs cube is modeled in order to determine the formation fracture pressure using the exploratory well cores and dipole sonic imager (DSI) Vs logs with a correlation coefficient of 0.95 for the Vs data obtained from the porosity, lithology, and primary DSI data. The vertical seismic profiling (VSP) data introduce a maximum interval velocity of 2760-2900 m/s in the field related to the Gotnia formation. The final amounts of seismic acoustic impedance inversion (AI) at the bottom of the field are mostly in the range of 8000-15000 [(m/s)*(g/cm3)], which can be related to the calcareous formations. Based on the Logratio matrix obtained from the fractal velocity-volume (Vp-V) model, the maximum overall accuracy (OA) in the dominant limestone intervals is 0.74. It indicates a high correlation of the Vp cube model obtained from the combination of sequential Gaussian simulation (SGS) and co-kriging models with AI. The uncertainty studies of Vp model in blind wells are about 50%, which is acceptable considering the large well numbers.
M. Mirzaie; P. Afzal; A. Adib; E. Rahimi; Gh. Mohammadi
Abstract
Detection of mineralized zones based on ores and gangues is important for mine planning and excavation operation. The major goal of this research work was to determine the zones based on ores and gangues by a combination of fractal and factor analysis in the Chah Gaz iron ore (Central Iran). The Concentration-Volume ...
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Detection of mineralized zones based on ores and gangues is important for mine planning and excavation operation. The major goal of this research work was to determine the zones based on ores and gangues by a combination of fractal and factor analysis in the Chah Gaz iron ore (Central Iran). The Concentration-Volume (C-V) fractal method was carried out for Fe, P and S, which indicated that the main mineralized zones consisted of the Fe, S, and P values ≥ 57%, ≤ 0.4%, and ≤0.3%, respectively. Factor analysis categorized variables in two groups including factor 1 (F1) and factor 2 (F2) for ore and gangue, respectively. The C-V fractal modeling on the derived factors showed four zones for F1 and F2. Based on the correlation among the results of fractal modeling on the elements and factors, the first and second zones of F1 were proper for exploitation. Furthermore, the last and first zones of F1 and F2 could be assumed as the main waste for mining excavation.
