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Quantitative Assessment of Resistivity Anisotropy in Evaluation of Laminated Shaly Sand Hydrocarbon Reservoirs–A Case Study in the Barents Sea, Norway

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Quantitative Assessment of Resistivity Anisotropy in Evaluation of Laminated Shaly Sand Hydrocarbon Reservoirs–A Case Study in the Barents Sea, Norway Tanzania Journal of Science 45(3): 450-462, 2019 ISSN 0856-1761, e-ISSN 2507-7961 © College of Natural and Applied Sciences, University of Dar es Salaam, 2019 Quantitative Assessment of Resistivity Anisotropy in Evaluation of Laminated Shaly Sand Hydrocarbon Reservoirs–A Case Study in the Barents Sea, Norway Ernest S Mulaya Department of Geology, University of Dar es Salaam, P. O. Box 35052 Dar es Salaam, Tanzania E-mail address: [email protected] Abstract Resistivity anisotropy in shaly sand lamination sequences affects the hydrocarbon evaluation in multiple dimensions of petrophysical logs. Currently, vertical resistivity (Rv) and horizontal resistivity (Rh) from 3D triaxial induction measurements can be applied simultaneously to resolve these petrophysical impacts. In this paper, an extensive analysis is offered with a focus on the hydrocarbon evaluation based on advanced petrophysical logs from a well. A critical analysis is done on the three comparable cases including clean formation as a base case, shaly sand case and laminated shaly sand case towards resolving resistivity anisotropy in a typical shaly sand laminated reservoir. The analysis results into potential pay zones of 38.0 m thick of gas and 76 m thick for oil. Furthermore, the results provide an increase in hydrocarbon pore fraction (HCPF) per depth up to 30% in zones with Rv/Rh ratio greater than or equal to 3 compared to conventional evaluation. The study concludes that in a lithology of shale sand laminated sequences, the feasible evaluation technique of hydrocarbon should involve the combination of derived hydrocarbon bearing sand lamina resistivity (Rsand) from horizontal (Rh) and vertical resistivity (Rv) of triaxial induction measurement, refined sand porosity from Thomas Stieber model and associated net to gross using the shaly sand models. Keywords: Resistivity anisotropy, laminated shaly sand, triaxial induction measurements, density magnetic resonance porosity, hydrocarbon evaluation Introduction of net pay and reliable assessment of Laminated shaly sands, as the name hydrocarbon saturation. implies, refers to alternating thin layers of Induction resistivity is based on the sands and shale leading to differences in their alternative currents in the transmitter coils vertical and horizontal electrical properties which set up an alternative magnetic field in (resistivity anisotropy) (Clavier et al. 1984, the conductive magnetic field (Ellis and Singer Worthington 1985, Herrick and Kennedy 1996, 2008). The effects of resistivity anisotropy on Ellis and Singer 2008). The laminated shaly the induction resistivity measurement have sand formations are very significant reservoirs been known since the 1950’s (Kunz and for oil and gas despite exhibiting ‘low Gianzero 1958, Moran and Gianzero 1979, resistivity pay’ (Worthington 2000, Clavaud et Anderson et al. 2008). The problems al. 2005). The increased content of shale associated with resistivity anisotropy become decrease the effective reservoir capacity acute in a thinly laminated shaly sand (Anderson et al. 1995, Gluyas and Swarbrick formation whose beds are thinner than the 2013). At the same time, the electrical vertical resolution of the conventional properties, i.e., conductivity of shales reduce resistivity and porosity measurement tools the formation resistivity, hence must be (Anderson and Gianzero 1982, Berg et al. corrected for the evaluations and identification 1996, Klein and Martin 1997, Mollison et al. 450 http://journals.udsm.ac.tz/index.php/tjs www.ajol.info/index.php/tjs/ Tanz. J. Vol. 45(3), 2019 1999, Schoen et al. 1999, Anderson et al. case, shaly sand case and laminated shaly sand 2008). The hydrocarbon saturation interpreted case from which the impact of resistivity from the conventional resistivity measurements anisotropy in laminated shaly sand reservoirs in these formation gives the cumulative or can further be refined and resolved both weighted average of the individual layers mathematically and petrophysically. This is response of both shale and sand lamina based on the vertical resistivity (Rv) and consequently lowering the hydrocarbon horizontal resistivity (Rh) from 3D triaxial estimation (Anderson et al. 1997). This is induction measurement towards maximizing because the computations involved are hydrocarbon evaluation. petrophysically dominated by high conductive shale/clay effects which obscure the presence Materials and Methods of more resistive hydrocarbon bearing sands Study area (Boyd et al. 1995, Fanini et al. 2001, This study used data from the exploration well Clavaud et al. 2005). 7220/8-1 located in the Southwestern Barents Therefore, this paper reports on three Sea, Norway (coordinates: 72° 29' 28.92'' N, comparable cases including clean formation 20° 20' 2.25'' E) (NPD 2019) (Figure 1). Figure 1: Geographical and geological location of the study area: (A) Geographical location of well 7220/8-1 at the Western Barents Sea (star in a square). (B) Tectonic framework of the Barents Sea region, the well 7220/8-1 drilled just west of the Polheim Sub- platform and Loppa High (Gabrielsen et al. 1990, Lřseth et al. 2013). Data availability, software loading and acquired by Schlumberger from a well in the quality control Barents Sea were interpreted using The input well logs data in Digital Log Techlog™ software (Techlog64 2013.4.0) Interchange Standards (DLIS format) licensed by Schlumberger Company. Data 451 Mulaya - Quantitative assessment of resistivity anisotropy sand hydrocarbon reservoirs … quality were checked for their reliability and (3) addressed leading to the initial choice of the The solution for the two Equations (1) appropriate data sets, parameters and and (2) as suggested by Shray and Borbas feasible methodology. The well logs data (2001), Clavaud et al. (2005), Wang et al. used in this study were environmentally (2006) and Anderson et al. (2008) can be corrected during logging hence no further mathematically simplified in Equations (4) corrections were made. and (5) below; Triaxial induction (Rv/Rh) values ( ) (4) Vertical resistivity (Rv) and horizontal resistivity (Rh) values from 3D triaxial ( ) (5) induction tool inferring electrical anisotropy were used to derive the true formation In mathematical sense, the following resistivity (Fanini et al. 2001, Wang et al. boundary conditions should be applied to 2006, Anderson et al. 2008). The triaxial obtain a continuous computation versus measured value is based on the fact that depth of the formation fluid volumes to when the measurement is made parallel to avoid blow ups according to Shray and the sand-shale layers, the results are similar Borbas (2001); to measuring resistance in parallel while i. The computed value of Rh should when the measurement is made across the not be equal to Rsh. lamination stacks the measured value is ii. The computed value of Rsnd should similar to measuring resistance in series not be equal to our picked Rsh. (Shray and Borbas 2001). The large difference between vertical resistivity (Rv) Resistivity of shale (Rsh) and sand (Rsnd) and horizontal resistivity (Rh) is an The resistivity of shale is an integral indication of resistivity anisotropy (Shray component of shaly sand saturation models. and Borbas, 2001, Clavaud et al. 2005, The value of shale resistivity (Rsh) of 3 ohm Anderson et al. 2008). For a laminated sand- m was estimated from the adjacent pure shale sequence, the portion of the reservoir shale zone between 1249.7 and 1276.0 m, that is of interest is the one with the zone assumed to be 100% shale. This hydrocarbon bearing sand package whose value was used to solve for Rsnd and volume resistivity (Rsnd), volume of shale (Vsh) and of sand (Vsnd) in Equations (4) and (5). On volume of sand (Vsnd) were derived from the the other hand, the resistivity of sand (Rsnd) methodologies illustrated by Shray and derived from triaxial values (Rv/Rh) was Borbas (2001), Clavaud et al. (2005) and calculated using Equation (4) in TechlogTM Anderson et al. (2008) as shown in the software. The results were simultaneously following section. used to calculate sand fraction (Vsnd) in Resolving sand resistivity involves Equation (5). initial inputs of horizontal resistivity (Rh) and vertical resistivity (Rv) derived from Resistivity of water (Rw) triaxial induction tool in Equations (1) and Rw is an integral part and interpretation (2) with additional argument in Equation (3) parameter used in calculation of all below; saturations (water and/or hydrocarbon) from the resistivity logs. Therefore, Rw was (1) computed based on resistivity ratio method under which the formation was partitioned (2) into flushed and noninvaded zone having the Where: same formation factor (F) but each 452 Tanz. J. Vol. 45(3), 2019 containing water of different resistivity ( ) ( ) measured from petrophysical logs using (7) Equation 6 (Archie 1942 and Peveraro While simultaneously the TCMR porosity is 1992). given as; ( ) ( )( ) (8) (6) Where; = measured formation bulk density 3 (g/cm ); = formation matrix density The Equation 6 above was applied in a 3 (g/cm ); = density of liquid phase in the water zone where both water saturation in 3 uninvaded formation (Sw) and in fully flushed zone at reservoir conditions (g/cm ); flushed zone (Sxo) are 100% with their = density of gas at reservoir conditions 3 respective resistivity denoted as Rt and Rxo. (g/cm ); = total formation porosity; ( ) = The Rxo/Rt ratio was calculated over the hydrogen index of liquid phase in the interval evidently most clean and fully flushed zone at reservoir conditions; ( ) = invaded water sand. Using the resistivity of hydrogen index of gas at reservoir mud filtrate (Rmf) as reported on log header, conditions, = flushed-zone gas the Rw was calculated. At a depth interval of saturation. 1414.5 - 1420.0 m an average Rt, average Rxo and Rmf at maximum recorded temperature ( ) (9) (extracted from logs header) were 0.6 ohm m, 1.5 ohm m and 0.132 ohm m, Where; = wait time for CPMG pulse respectively. Hence a value of 0.053 ohm m sequence (s); = gas longitudinal relaxation time at reservoir conditions (s). was used as Rw input for computations throughout this study (Equation 6a).
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