SPATIAL DISTRIBUTION OF POROSITY IN EOCENE CARBONATE RESERVOIR UPPER INDUS BASIN PAKISTAN

Abstract

Porosity is the most important factor in evaluating reservoirs. Porosity extraction from seismic data is an extremely difficult task that is subject to ambiguity for a variety of reasons. For the extraction of porosity from seismic data, seismic inversion is used. The main theme of this research project is to show the spatial distribution of total and effective porosity at the reservoir level and also to compare the results of Model-based and Sparse-spike inversion. Further aim of evaluating the reservoir porosity used in this dissertation is the seismic attributes. The amplitude, shape, and position of a seismic waveform are commonly described by seismic attributes. The attributes considered in this dissertation are limited to fracture identification, orientation, and intensity of the fracture at reservoir level. In this research, 3D seismic data were firstly used to mark horizon with the help of synthetic seismogram then time and depth contour map of the Chorgali and Sakessar formation were generated which confirm that time and depth is increasing towards NW and decreasing towards SW. Well log data of Balkassar OXY-1 well was used to calculate porosities and other reservoir properties of the Chorgali and Sakessar formation of Balkassar area, Pakistan's Upper Indus basin. No zone for Hydrocarbon accumulation is present in the Chorgali and Sakessar formation, only a small zone of 3m between 2424 to 2427 were marked at Chorgali level containing 44% hydrocarbon and 56% water saturation with a total porosity of 27% and effective porosity of 25%. To examine the fracture density and orientation as well as the hydrocarbon saturation, the fracture attributes were applied to a Chorgali and Sakessar level. According to the attribute results, there is a very little fracture density at the Chorgali and Sakessar levels, where the OXY-1 well is drilled, and there is a considerable density of fractures at the Chorgali level to the South-East of the OXY-1 well. The well log data and the interpreted horizon were then used in Model-based and Sparse-spike inversion to better visualize the seismic data in the form of acoustic impedance. Acoustic impedances were very high at the location of the well OXY-1 but adjacent areas to the south west on the same inline 90 but cross line 266 shows from the result of both Model-based and Sparse-spike inversion that it has a very low impedance. however, when compared the results of both method, Model-based were more pronounced than the result of the Sparse-spike inversion. A geostatistical method was applied to extract the total and effective porosity from the acoustic impedance derived from both the Model-based and Sparse-spike inversion. After this slices of DRSML QAU 13 porosities were created to check the spatial distribution of porosities at Chorgali and Sakessar level. This spatial distribution of porosity also suggested that that there is very low porosity zone at both Chorgali and Sakessar level where the OXY-1 well is drilled the high porosity zone is exactly to the SW of the well Balkassar OXY-1 on the same inline 90 but cross line 266 at Chorgali level. Low acoustic impedance models were constructed using well-log data. The use of well-log data allows for the calibration of reservoir porosity with inverted acoustic impedance. The spatial porosity distribution within the Chorgali and Sakessar formation is accurately estimated by the results of Model-based inversion and Sparse-spike inversion. Following post stack inversion, the total and effective porosity at Chorgali level is 11% and 9%, compared to 4% and 2% at Sakessar level respectively. Porosity values predicted from the seismic data via Probabilistic Neural network were in good agreement with the porosity derived from the well log data. The methodology used in this dissertation can be applied to a similar basin in Asia and across Pakistan having same geology and structural setting