Static Reservoir Modeling Using Well Log and 3-D Seismic Data in a KN Field, Offshore Niger Delta, Nigeria

Abstract

This study focuses on the application of 3D static model using 3-D seismic and well log data for proper optimization and development of hydrocarbon potential in KN field of Niger Delta Province. 3D Seismic data were used to generate the input interpreted horizon grids and fault polygons. The horizon which cut across the six wells was used for the analysis and detailed petrophysical analysis was carried out. Structural and property modeling (net to gross, porosity, permeability, water saturation and facies) were distributed stochastically within the constructed 3D grid using Sequential Gaussian Simulation and Sequential Indicator Simulation algorithms. The reservoir structural model show system of different oriented growth faults F1 to F6. Faults 1 and Fault 4 are the major growth faults, dipping towards southwest and are quite extensive. A rollover anticline formed as a result of deformation of the sediments deposited on the downthrown block of fault F1. The other faults (2, 3, 5 and 6) are minor fault (synthetic and antithetic). The trapping mechanism is a fault assisted anticlinal closure. Results from well log analysis and petrophysical models classified sand 9 reservoir as a moderate to good reservoir in terms of facies, with good porosity, permeability, moderate net to gross and low water saturation. The volumetric calculation of modeled sand 9 horizon reveals that the (STOIIP) value at the Downthrown and Ramp segment are 15.7 MMbbl and 3.8 MMbbl respectively. This implies that the mapped horizon indicates hydrocarbon accumulation in economic quantity. This study has also demonstrated the effectiveness of 3-D static modeling technique as a tool for better understanding of spatial distribution of discrete and continuous reservoir properties, hence, has provided a framework for future prediction of reservoir performance and production behavior of sand 9 reservoir. However, more horizontal wells should be drilled to enhance optimization of the reservoir.

Petro physical parameter studies for characterization of gas reservoir of Narsingdi gas field, Bangladesh

“…According to porosity calculation, zone-4 is the most prospective gas-bearing zone with respect to zone1, 2, 3, and 5 in the study well. Some recent studies were found also similar average porosity ranged in the Laja Oil Field, Rickie Field, KN Field and Y Field, Niger delta [27][28][29][30]. For assessing Narsingdi gas productivity, the calculated average permeability values of these zones were ranged from 28 mD to 90 mD by Coates and Domanior [19] equation while average permeability values ranged From 28 mD to 40 mD was followed by Wyllie and Rose [20] equation.…”

Integrated geologic, geophysical, and petrophysical data to construct full field geologic model of Cambrian-Ordovician and Upper Cretaceous reservoir formations, Central Western Sirte Basin, Libya

“…Integrating geologic, geophysical, and petrophysical data into one complete model of the whole field is an important process to help better understand the complexity of reservoir formations, thereby facilitating significant gains in productivity in terms of identifying and managing reservoirs (Zou et al, 2006;Denney, 2013;Adeoti et al, 2014). It provides reservoir engineers with a reliable and comprehensive basis upon which they can simulate and manage reservoirs (Al-Harbi et al, 2013;Karamitopoulos et al, 2013).…”

Reservoir Petrophysical Modeling and Risk Analysis in Reserve Estimation; A Case Study from Qasr Field, North Western Desert, Egypt

“…The study has also created a geological model for KN field that can be updated as new data are acquired for field development. The model could be transferred to the reservoir engineer for proper characterization during simulation [2]. The quality of petrophysical analysis leads to a better reserve calculation [3][4][5].…”