2-DIMENSIONAL INTEGRETED SEISMIC INTERPRETATION OF REFLECTION DATA, ATTRIBUTE ANALYSIS, PETROPHYSICAL AND ROCK PHYSICS BASED FACIES ANALYSIS OF DHANDI AREA

Abstract

The main purpose of the study is to evaluate hydrocarbon potential of Dhandi area that lies in Punjab near Rahim Yar Khan, Central Indus basin for delineation of potential leads for future prospects. This is done by the analysis of 2-D seismic and wire line log data, which have been provided by Landmark, Pakistan with the permission of Directorate General of Petroleum Concessions, Islamabad, Pakistan. This data set comprises of 6 seismic lines and a complete suite of wire line logs of 1 well SABZAL-01. The seismic data is utilized for the identification of structural traps, marking of the different lithological horizons and naming them using the well tops data in the area. There are no faults demarcated on seismic lines as the area of study is very stable and doesn’t contain faults. On the seismic section, three prominent reflectors are marked namely Ghazij Formation, Sui Main Limestone and Upper Ranikot Formation. Two-way time contour maps of the marked lithologies have been prepared to determine the spatial variation of time. Root mean square velocity models are generated to observe the variation of velocities with time in the subsurface. Depth contour maps are also generated for these marked lithologies. Analysis of wire line logs includes the calculation of different reservoir characteristics like Shale Volume (Vsh), Porosity (Phi), True Resistivity of Formation (Rt), Density (RHOB), Water Saturation (Sw), Hydrocarbon Saturation (Shc) etc., using different available Logs such as Gamma Ray, LLD, LLS, Litho Density Log, and Spontaneous Potential Log. These measured Parameters, then, used further for reservoir potential evaluation. Sui Main Limestone Formation is the primary reservoir in this area. A zone of 11 meters is marked in this region. The well log data is also used for Rock Physics analysis to compute elastic logs that are cross plotted for facies modeling.