Integration of 3D-seismic and petrophysical analysis with rock physics analysis in the characterization of SOKAB field, Niger delta, Nigeria

Abstract

Compartmentalization of reservoirs and technical failures experienced in data acquisition, processing and interpretation, without doubt, hinder the effective characterization of reservoirs. In this research, to ensure accuracy, three methods were integrated to characterize reservoirs in SOKAB field. Petrophysical analysis, seismic interpretation, and modeling, and rock physics analysis were utilized. Its objectives were: to develop a template to facilitate improvements in future reservoir characterization research works and producibility determination; to utilize rock physics models to quality check the seismic results and to properly define the pore connectivity of the reservoirs, and to locate the best productive zones for future wells in the field. Forty-three faults were mapped and this included five major faults. Two hydrocarbon bearing sand units (A & B) were correlated across five wells. Structural maps were generated for both reservoirs from which majorly fault assisted and dependent closures were observed. The petrophysical analysis indicated that the reservoirs have good pore interconnectivity (Average Ф effective = 23% & 22% and K average = 1754md & 2295md). The seismic interpretation and modeling alongside the petrophysical analysis were then quality checked via qualitative rock physics analysis. From the K dry /Porosity plot, the sands were generally observed to lie within the lower Reuss and upper Voigt bound which indicates a low level of compaction. From the velocity-porosity cross plot, it was revealed that the lower portions of the reservoirs were poorly cemented and this could hinder their producibility.

Three-dimensional Structural Modeling (3D SM) and Joint Geophysical Characterization (JGC) of Hydrocarbon Reservoir: A Case Study of the Kadanwari field in Middle Indus Basin (MIB), Southeastern Pakistan

“…Reservoir characterization is a scheme that quanti es the physical and uid properties of rock, such as lithology, volume of shale (V shale ), average porosity (∅ avg ), effective porosity (∅ eff ), permeability (K), water saturation (S W ), and hydrocarbon saturation (S hc ) (Bodunde and Enikanselu, 2019;Kargarpour, 2020;Qadri et al, 2020;Ahmad et al, 2021;Hossain et al, 2021;Khan et al, 2021;Thota et al, 2021). It also includes understanding of reservoir structure, sedimentological heterogeneity, facies, and quantity of hydrocarbon that may exist in structural traps driven by tectonic movements, discontinuities like faults, folds anticlinal structures, horst and graben pop up geometries, and duplex structures (Haque et al, 2016;Li et al, 2018;Osinowo et al, 2018;Qadri et al, 2020;Saif-Ur-Rehman et al, 2020;Abdeen et al, 2021;Islam et al, 2021;Khan et al, 2021;Mutebi et al, 2021;Thota et al, 2021).…”

“…It also includes understanding of reservoir structure, sedimentological heterogeneity, facies, and quantity of hydrocarbon that may exist in structural traps driven by tectonic movements, discontinuities like faults, folds anticlinal structures, horst and graben pop up geometries, and duplex structures (Haque et al, 2016;Li et al, 2018;Osinowo et al, 2018;Qadri et al, 2020;Saif-Ur-Rehman et al, 2020;Abdeen et al, 2021;Islam et al, 2021;Khan et al, 2021;Mutebi et al, 2021;Thota et al, 2021). The advancement in 3D seismic re ection surveys and borehole geophysics has made it possible to characterize structural and stratigraphic features and associated petrophysical properties with a high reliability and precision, thereby reducing the risk associated with hydrocarbon exploration (Gao, 2011;Abuamarah et al, 2019;Bodunde and Enikanselu, 2019). Employing more than one tool to derive a consistent answer enables both precision and accuracy.…”

“…Employing more than one tool to derive a consistent answer enables both precision and accuracy. Therefore, reservoir characterization (e.g., evaluation of structural and stratigraphic features, distribution of associated petrophysical properties and facies) can be better comprehended by employing integrated seismic interpretation-aided 3D structural modeling (SM), 3D seismic attribute analysis, and petrophysical modeling (Czoski, 2014;Hussain et al, 2017;Li et al, 2018;Ashraf et al, 2019;Bodunde and Enikanselu, 2019;Radwan, 2021;Radwan et al, 2021;Thota et al, 2021). 3D SM is divided into the entity-based modelling and volume-based modelling (Houlding, 1994;Lajaunie et al, 1997;Mallet, 2002;Wu et al, 2005;Zhang et al, 2018;Wang et al, 2019).…”

Three-dimensional Structural Modeling (3D SM) and Joint Geophysical Characterization (JGC) of Hydrocarbon Reservoir: A Case Study of the Kadanwari field in Middle Indus Basin (MIB), Southeastern Pakistan

“…Reservoir characterization is a scheme that quantifies the physical and fluid properties of rock, such as lithology, volume of shale (V shale ), average porosity (∅ avg ), effective porosity (∅ eff ), permeability (K), water saturation (S W ), and hydrocarbon saturation (S hc ) [1,2,6,[8][9][10][11]. It also includes understanding of reservoir structure, sedimentological heterogeneity, facies, and quantity of hydrocarbon that may exist in structural traps driven by tectonic movements, discontinuities like faults, folds anticlinal structures, horst and graben pop up geometries, and duplex structures [1,2,7,8,[12][13][14][15][16][17].…”

Petrophysical interpretation and fluid substitution modelling of the upper shallow marine sandstone reservoirs in the Bredasdorp Basin, offshore South Africa

“…The Gassmann fluid substitution method is probably the most well-known rock physics model, and it is used to predict how P and S waves change as saturation changes (Purnamasari et al 2014). Modelling the changes in the elastic properties is possible mainly because of the huge sensitivity of the bulk modulus to saturation changes (Bodunde and Enikanselu 2018). In this study, Gassmann fluid substitution model was applied in well log and rock physics model.…”