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A workflow for reservoir characterization applied to presalt coquinas from the Linguado Field, Campos Basin, Brazil
Journal of Petroleum Science and Engineering 183 (2019) 106451
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A workflow for reservoir characterization applied to presalt coquinas from the Linguado Field, Campos Basin, Brazil
T
Alessandra Alves Peçanhaa,∗, Wagner Moreira Lupinaccia,b, Danilo Jotta Ariza Ferreiraa,c, Antonio Fernando Menezes Freirea a
Universidade Federal Fluminense, Department of Geology and Geophysics (GIECAR), Av. General Tavares de Souza, Niterói, RJ, 24210-346, Brazil Universidade Federal Fluminense, Biomass and Water Management Research Center (NAB), R. Prof. Edmundo March, S/n, Boa Viagem, Niterói, RJ, 24210-330, Brazil c Schlumberger, Software Integrated Solutions, Av. República Do Chile 330, RJ, 20031-170, Brazil b
A R T I C LE I N FO
A B S T R A C T
Keywords: Reservoir characterization Presalt Geobody Porosity modeling Acoustic inversion Coquinas
Characterization of presalt coquinas reservoirs is a know challenging task due to its facies and, consequently, petrophysical properties heterogeneity and anisotropy. This fact makes the traditional seismic interpretation and well log analysis workflow not enough for the interpreter to address reasonably the reservoir complexity. In this study, a methodology integrating different geological and geophysical interpretation techniques based on data pre-conditioning, model-based seismic acoustic inversion, effective porosity geostatistical modeling using sequential gaussian simulation with collocated co-kriging and geobody interpretation is proposed to obtain maximum information from the available data which consists on post-stack seismic and well logs from the lacustrine coquinas carbonate reservoirs from the Coqueiros Formation located in the Linguado Field on Campos Basin. Acoustic seismic inversion results allowed the interpretation of four new seismic horizons that could individualize two coquinas intervals and effective porosity modeling results allowed the geobody extraction of the coquinas banks that represent the best reservoir facies within the study area with effective porosities between 13 and 30% making it even possible to identify new exploratory areas. Therefore, the proposed workflow is very reliable for coquinas reservoirs characterization and can be applied in other areas.
1. Introduction The Linguado Field is in the southwest region of Campos basin. It has four main reservoirs represented by sandstones from the Carapebus Formation, marine carbonates from the Quissamã Formation, lacustrine carbonates from the Coqueiros Formation and fractured basalts from the Cabiúnas Formation (Winter et al., 2007), also known as the economic basement which represents the limit in which below there are no longer rocks that are viable hydrocarbon reservoirs. The Coqueiros Formation, focus of this study, was deposited in a lacustrine setting during the Barremian to the beginning of the Aptian. Comprises intercalations of organic matter rich shales, Campos basin main source rock, and coquinas banks composed mainly of bivalve mollusk shells that represent the formation reservoirs. The coquinas rocks have been extensively studied by several authors over the years (Schaller et al., 1981; Bertani and Carozzi, 1985; Carvalho et al., 2000; Castro, 2006; Mello, 2008), however their characterization is still very challenging because of its unique faciological heterogeneity, anisotropy and
diagenetic evolution making it difficult to predict petrophysical properties distribution and, consequently infer reservoir quality (Bruhn et al., 2003; Thompson et al., 2015). In the Linguado Field, the coquinas sequences are composed by the sedimentation of grainstones, packstones, rudstones in coarsening upwards cycles, with average porosities between 15 and 20% and medium permeabilities varying from less than 1mD to more than 500mD with an average thickness of 100 m (Horschutz et al., 1992; Castro, 2006, Bernardes Oliveira et al., 2019). Coquinas intervals were divided by Schaller et al. (1981) into upper and lower banks that are usually separated by fine grained rocks such as shale, silt, and marl, and represent two distinct depositional stages. The lower coquinas interval presents thicknesses of 75 m–150 m composed by bioclastic deposits intercalated with thin layers of sandstone and shales constituting the main exploratory interval of the Linguado Field. As for the upper coquinas interval, it has lower porosity and thickness, 30 m in average, representing secondary reservoirs within the Coqueiros Formation (Tigre et al., 1983). The paleoenvironmental
∗
Corresponding author. E-mail addresses: [email protected] (A.A. Peçanha), [email protected]ff.br (W.M. Lupinacci), [email protected] (D.J.A. Ferreira), [email protected]ff.br (A.F.M. Freire). https://doi.org/10.1016/j.petrol.2019.106451 Received 13 May 2019; Received in revised form 29 July 2019; Accepted 28 August 2019 Available online 03 September 2019 0920-4105/ © 2019 Elsevier B.V. All rights reserved.
Journal of Petroleum Science and Engineering 183 (2019) 106451
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Fig. 1. Location map of the wells and seismic data available for the study in the Linguado Field, Campos Basin. Also, IL = inline 1570 and AB = arbitrary seismic section position can be observed.
Fig. 2. Proposed workflow for the individualization and characterization of the coquinas banks.
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Fig. 3. Seismic section of inline 1570 a) uninterpreted and b) interpreted.
study. In the seismic interpretation stage, the economic basement top and evaporite sequence base, Retiro Formation, seismic unconformities (Winter et al., 2007) that delimit the stratigraphic interval in which coquinas are included within Linguado field were interpreted coupled with main rift phase faults to create a structural-stratigraphic model of the Lagoa Feia Group, that in the case of Linguado field is mainly composed by Coqueiros Formation. This model helped to understand the compartmentalization of the area and served as input for porosity modeling. The TecVa, amplitude volume technique, attribute was used as a tool to aid in the interpretation of seismic horizons and, especially, faults (Bulhões and Amorin, 2005). This seismic attribute transforms the amplitude into a pseudo relief, which helps in the visualization and mapping of horizons and faults. The seismic data preconditioning workflow applied to improve resolution and increase the signal-to-noise ratio, before performing seismic inversion and porosity modeling, was based on the work of Lupinacci et al. (2017) and consisted into three stages: curvelet filtering, inverse Q filtering, and band pass filter up to 60 Hz. Seismic well tie was performed in the interval of the Lagoa Feia Group. In this step, the base, economic basement, and top, evaporites base, horizons of the Lagoa Feia Group were used as input data along with markers, sonic and density well logs, checkshots and the preconditioned seismic data. The objective of this step was positioning of the wells in time with the seismic data trying to get the best correlation factor between synthetic and real seismic traces to be able to perform an optimum seismic inversion. After this stage, the acoustic impedance logs were filtered up to 10 Hz to be extrapolated to construct the initial acoustic impedance model for seismic inversion, which had as guides the top and base horizons of the Lagoa Feia Group. Well 1-RJS-74-RJ was removed from
evolution that define the two levels of coquinas transitions from alluvial fans to lacustrine deposits (Thompson et al., 2015). According to the Brazilian National Petroleum Agency, Linguado field together with three other adjacent fields in the region, Badejo, Trilha and Pampo, produces 16,000 bbl/day of oil and 5 mm3/day of natural gas from the Pampo-1, P-7, and P-12 platforms, which are connected to 45 production wells. In 1985, 1994, were registered the higher production peaks of oil and natural gas, respectively, thus the Linguado Field is considered a mature hydrocarbon field with production in decrease since then. Therefore, the aim of this study is to propose a workflow for the individualization and characterization of the two coquinas reservoir intervals in the Linguado Field to better address its complexity based on the seismic, well and rock sample data integration and to provide efficient tools for seismic interpretation, porosity modeling and geobody extraction of coquinas banks in the study area. Available data was composed of 13 wells data and 65 km2 of 3D post-stack seismic data within the field area (Fig. 1). 2. Methodology The proposed workflow for characterization of the coquinas banks carbonate reservoirs from the Coqueiros Formation was divided into five main stages: (1) study interval seismic interpretation and structural model and grid construction; (2) seismic data preconditioning to increase resolution and signal to noise ratio; (3) acoustic inversion using model-based inversion method (Russell and Hampson, 1991, 2006); (4) porosity modeling through sequential gaussian simulation geostatistical method with colocalized co-kriging using the acoustic impedance results (Pyrcz and Deutsch, 2014; Azevedo and Soares, 2017); (5) coquinas intervals geobody extraction, using as main criteria the porosity contrast of these facies. Fig. 2 resumes the workflow applied to this 3
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Fig. 4. (a) Map of the pre-evaporite unconformity with main faults, (top of the Lagoa Feia Group) and (b) 3D view of the basement and pre-evaporite unconformities (top and base of the Lagoa Feia Group) and faults constructed structural model for the area.
the construction of the initial model and inversion to be a quality control well for the seismic inversion results. Porosity modeling was then performed with the effective porosities, calculated in the wells, that were transformed to a gaussian distribution and, as the sample points, available well data, are sparse and irregular throughout the study area, and the construction of a gaussian variogram model was adjusted based on a great number of linear combinations tests for sample pairs in order to ideally describe the spatial correlation of sampled points coupled with geological conceptual models (Caers, 2005). After several trials, the direction NE-SW was defined as a direction of lowest variability, parallel to the regional rift fault directions of the Campos Basin, and the direction NW-SE as the direction of greatest variability and porosity modeling was performed through sequential gaussian simulation integrated with the colocalized co-kriging (Ziegel et al., 1998) using as secondary variable the acoustic impedance volume. Finally, a geobody was extracted from the porosity modeling volume that represents the facies of greater effective porosity, the
Table 1 Correlation factor of the well ties. Wells
Correlation Factor, %
1-RJS-74-RJ 1-RJS-49-RJ 3-LI-2-RJ 3-LI-4-RJS 3-LI-5-RJS 3-LI-8-RJS 3-RJS-157C-RJ 3-RJS-167-RJ 3-RJS-73B-RJ 4-RJS-139-RJ 4-RJS-156-RJ 7-LI-10 7-LI-3
71 77 72 56 76 78 85 63 72 75 79 85 77
4
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unconformity presents erosive truncation terminations with low to high positive amplitudes and lateral continuity depending on seismic quality. Below this reflector the seismic facies is chaotic. As for the reflector corresponding to the salt base unconformity, top of the Lagoa Feia Group, it is characterized by low to medium negative values of amplitude and fair lateral continuity. Seismic facies within the mapped interval are mostly plane parallel reflectors at the structural highs becoming more chaotic at the structural lows. The coquinas reservoirs were expected to be related to the plane parallel reflectors. A structural model and grid were generated after seismic interpretation and can be observed in Fig. 4a. The surfaces of this model show an apparent dip to the southeast towards the depocenter of Campos Basin (Fig. 4b). The two major rift faults, one in the eastern portion (AA’) and the other in the western portion (BB’), have N–S orientation and differ slightly from the usual NE-SW orientation for rift faults in Campos Basin. Faulting in the Linguado field are mostly normal faults with few antithetic associated. The largest fault localized in the east (AA’) divides the Lagoa Feia Group into a structural low to the east and a structural high to the west, with all wells located at the structural high. Seismic well tie within the Lagoa Feia Group interval was performed after the seismic data preconditioning and the correlation coefficients obtained for each well is shown in Table 1. The thirteen wells presented, in majority, correlation factors higher than 70%, a percentage considered acceptable for construction of the low frequency acoustic impedance model and the inversion itself. Also, the average of the wavelets estimated for the well tie process, except from 1-RJS-74-RJ quality control well, was created for posterior use for seismic inversion. Subsequently, seismic inversion was performed considering parametrization of number of algorithm interactions and acceptable acoustic impedance deviations values from the measured values from well logs. For quality control purposes, inversion results in the well locations are shown in Fig. 5 and a good correlation can be observed, in the interest interval, for the impedances of the well logs. For well 1-RJS74-RJ, used as a blind test, is also observed a good correlation between the original and inversion acoustic impedance values, which confirms that seismic inversion result is robust. The arbitrary section AB is shown in Fig. 6 to illustrate the acoustic impedance results and a division is clear within Lagoa Feia Group interval where the group upper portion presents medium to high acoustic impedance values and the lower part presents low to medium values. The aptian carbonate reservoirs, focus of this study, are represented mostly by the upper part of the Lagoa Feia Group. Therefore, the impedance contrasts and the chronostratigraphic markers of the wells allowed the identification and mapping of top and bottom of the upper and lower coquinas banks, as described in the literature by Schaller et al. (1981) and Baumgarten (1985), and the interpretation of two new seismic unconformities pre-Alagoas and pre-
Fig. 5. Comparison between the acoustic impedance (AI) logs (blue curve), the AI from the seismic inversion (red curve), and background AI model (black curve) at well locations. The interval of interest, Lagoa Feia Group, is limited by the yellow lines. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
coquinas banks, in the Coqueiros Formation. Cutoff points from 13% to 30% porosity were applied for the extraction. 3. Results Seismic interpretation results consisted in the mapping of the economic basement unconformity which separates the top of the Cabiúnas Formation from the base of the Lagoa Feia Group, the salt base unconformity which separates the base of the Retiro Formation from the top of the Lagoa Feia Group and main faulting. These interfaces are shown in seismic section of Fig. 3. The seismic reflector that corresponds to the economic basement
Fig. 6. Arbitrary section AB with acoustic impedance values, passing through wells 3-RJS-73B-RJ, 1-RJS-49-RJ and 3-LI-8-RJS. 5
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Fig. 7. Simplified chronostratigraphic chart of the Campos Basin focusing on the presalt interval.
Fig. 8. Acoustic impedance in inline 1570 with interpreted horizons.
The last mapped horizon is the top of the upper coquinas bank which also represents the top of the Coqueiros Formation, also known as the pre-Alagoas unconformity and the end of the rift phase. This horizon separates the coquinas sequence from the Macabu Formation (Winter et al., 2007), an interval where slightly higher acoustic impedance values are noted, ranging from 9000 to 11,000 m/s × g/cm3. Finally, the pre-evaporite unconformity is well marked by the start of higher acoustic impedance values above 11,000 m/s × g/cm3 and represents the beginning of the Retiro Formation evaporites. The acoustic impedance projected over the top of the lower coquinas bank is shown in Fig. 9a. This map view shows that, in general, the reservoir facies, where the wells were drilled, are regions with the lowest values of acoustic impedance. In Fig. 9b, the acoustic impedance is shown on the top of the upper coquinas banks and it can be noted that the wells were drilled in places where acoustic impedance values are slightly higher when compared to lower coquinas banks. The clay volume, effective porosity, water saturation and net to pay intervals were calculated using well logs and these results are shown for the wells 3-LI-2-RJS, 1-RJS-74-RJ and 1-RJS-49-RJ in Fig. 10. Based in the petrophysical evaluation, it was observed low clay content (low presence of marls, shales and mudstones) and high values of effective porosity in the lower coquinas level, where mean effective porosities are of 15%, and can reach maximum of 30%. This level presents a considerable thickness of reservoir rock, greater than 100 m in most of the wells analyzed (Fig. 10a) and it is also where the largest net to pay thicknesses are observed, as shown in well 1-RJS-49-RJ (Fig. 10c). In
Jiquiá (Winter et al., 2007). The base of Coqueiros Formation horizon represents the LF-35 stratigraphic marker from the wells which is the base of the lower coquinas bank identified in the literature as the limit between the lower siliciclastic talc-stevensite sequence and mixed siliciclastic-carbonate coquinas sequence (Mohriak et al., 1990; Karner and Gamboa, 2007). A simplified chronostratigraphic chart focusing on the presalt interval with its main unconformities is shown in Fig. 7. Fig. 8 shows all the seismic horizons interpreted using acoustic impedance results. In order to map the base of Coqueiros Formation horizon, it was observed a high contrast of acoustic impedance between the upper portion of the talc-stevensite sequence which presents medium acoustic impedance values (from 8000 to 10,000 m/s × g/cm3), compared to the basal portion of the coquinas sequence, which presents considerably lower acoustic impedance values (from 6000 to 8500 m/s × g/cm3). The pre-Jiquiá unconformity was mapped using as reference the upper limit of lower coquina bank that contrasts with higher acoustic impedance values above it. This seismic horizon divides the Coqueiros Formation into two distinct depositional phases, separated by the sedimentation of the Jiquiá shale (Horschutz et al., 1992) that presents high acoustic impedance values varying from 9000 to 14,000 m/s × g/ cm3. The base of the upper coquinas banks was also mapped, consequently, because of the contrast with the Jiquiá shale higher acoustic impedance values since it has lower impedance values, around 6000 and 8500 m/s × g/cm3, when compared to it. 6
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Fig. 9. Maps with acoustic impedance on the tops of the Lower Coquinas (a) and the Upper Coquinas (b).
coquinas bank does not constitute an important exploratory target due to the presence of many finer facies such as packstones and wackestones deposited in a moderate to low energy environment, that usually become a hydrocarbon flow barrier. After well logs evaluation, a structural model between the preJiquiá and pre-evaporite unconformities considering the mapped faults was constructed and then gridded with 10 layers for the porosity modeling. The effective porosity logs were used for the porosity modeling with the acoustic impedance volume as a secondary variable. The obtained results can be seen in Fig. 11 and presented an average effective porosity of 12.8%. The effective porosity over the top of the lower coquinas bank is
the lower coquinas level is reported a greater incidence of pure coquinas, rudstones and bioclastic grains, defined by Castro and Azambuja Filho (1981) which are the highest energy facies within Coqueiros Formation and represent the main reservoir for the study area. The upper coquinas bank has an average effective porosity of 12%, however in some wells the porosity is almost null, as is the case of well 1-RJS-74-RJ (Fig. 10b). The gross is considerably lower than that observed in the lower coquinas bank, not reaching values greater than 30 m. Also, it is more heterogeneous, presenting numerous intercalations with finer sediment rocks, which results in zones with lower permoporous characteristics. The net to pay intervals are thinner or even absent in some wells. According to Bizotto (2014), the upper
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Fig. 10. Logs evaluation in well 3-LI-2-RJS (a), 1RJS-74-RJ (b) and 1-RJS-49-RJ (c). Track 1: depth in meters; Track 2: Coqueiros Formation interval; Track 3: lithological log; Track 4: clay volume (VShale); Track 5: total porosity (PHIT) and effective porosity (PHIE); Track 6: water saturation (Sw); Track 6: net-pay intervals. Highlighting the coquinas levels: upper coquinas (green rectangle) and Lower Coquinas (blue rectangle). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 11. Porosity modeling results for the Coqueiros Formation using the Sequential Gaussian Simulation method with colocalized co-kriging.
sub commercial well, is in an area with relatively high porosity, but after petrophysical evaluation it was considered to be below oil water contact, which explains its non-commerciality. As for well 1-RJS-49-RJ, also classified as non-commercial, it is positioned on a location with low effective porosity. The porosity map on the upper coquinas level (Fig. 12b) also has
shown in Fig. 12a, and as can be observed several portions present very porous facies and, consequently almost all wells were drilled in regions with high porosity values. Even the wells 3-LI-8-RJS; 3-LI-2-RJS; 1-RJS49-RJ and 3-LI-4-RJS, which were not drilled in locations where effective porosities as high as the others, still have a reasonable porosity and are classified as producing wells. Well 1-RJS-74-RJ, identified as a 8
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Fig. 12. Porosity maps of the Lower Coquinas (a) and Upper Coquinas (b).
levels. Ratifying the acoustic impedance results, the effective porosity maps over the top of upper and lower coquinas banks show that there is a large concentration of wells in the central field part and few wells drilled at low porosities for both intervals but mostly in the upper coquinas portion. Most of the wells were drilled in regions with an average porosity of 12%, as can be seen in Fig. 12 but there are regions
porous facies values similar to those found in the lower coquinas level, but the regions with these facies are smaller and discontinuous than those observed in the lower bank. Well 1-RJS-74-RJ also indicates low porosity at this coquinas level. The fact that this well is non-producing is explained by the higher water saturation in the more porous regions, and low porosities in the other intervals, besides having a layer of small thickness, impacting low gross and low net to pay at both the coquinas 9
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sediment content. A zoning of the more porous regions was possible with the geobody, allowing the predictability of facies of high energy lake environment, which composed the main lacustrine reservoirs of the rift phase.
4. Discussion Some areas of greater porosity occur at the edge of the large fault AA’ in Fig. 4a, which indicates that the sin-depositional tectonism may have been the mechanism responsible for the high porosities favoring the access of meteoric water in those regions causing dissolution and increasing interparticle spaces. In Fig. 12a, the lower coquinas bank presents an area with few wells drilled near of this fault, with high porosity values. This fact may be because even though this region have good reservoir rock characteristics, it is possible that due to the presence of faulting, active tectonism may have prevented the formation of a seal. The vertical heterogeneity observed in the Coqueiros Formation is the result of several depositional shallowing upward cycles which composed the two coquinas levels reflecting the continuous increase of energy in the depositional environment, culminating in the deposition of coquinas at the top of each phase (Bizotto, 2014). Fig. 14 shows the well correlation for wells 3-LI-02-RJS, 1-RJS-74RJ, 3-RJS-73B-RJ and 1-RJS-49-RJ. Along the Coqueiros Formation, the reduction of coarse-grained clastic sediments, such as sandstone and conglomerate, and the increase of marl and shale intercalations is observed from wells 3-LI-02-RJS to 1- RJS-49-RJ. This may indicate that since well 3-LI-02-RJS was drilled near a fault edge, contemporary tectonism to sedimentation caused more clastic sediments to occurs whereas, in well 1- RJS-49-RJ, there was a higher water column and lower tectonic activity during the sedimentation that made it possible for the coquinas sequences deposition. When comparing the depositional model suggested by Guardado et al. (1989), for lacustrine carbonates of the Coqueiros Formation, the
Fig. 13. Geobody extracted from the porosity model cutoffs where green colors represent porosities between 13% and 30% and yellow to red colors represent porosities between 30% and 35%. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
with effective porosities up to 20%–30%, which do not yet have drilled wells. Finally, a geobody was extracted based on the effective porosity values obtained from the geostatistical modeling (Fig. 13) using the cutoff range of 13%–30%. This geological body was constructed to individualize the most porous facies, especially the coquinas banks associated with high values of porosity. According to the evaluation of the logs, marl, shale, silt, mudstones and wackestones facies are the ones that have the lowest effective porosity, mainly due to high finer
Fig. 14. Correlation of wells 3-LI-2-RJS, 1-RJS-74-RJ, 3-RJS-73B-RJ and 1-RJS-49-RJ, with emphasis on the Coqueiros Formation lower coquinas (C.I) and upper coquinas (C.S) banks. 10
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geobody very closely resembles the carbonate banks of isolated coquinas over basement structural highs. Also, as described by Carvalho et al. (2000), these carbonate banks have aggradational deposition and lateral facies transition to finer facies and with low effective porosity, such as shale and silt. The regions absent in the geobody represent more abundant accumulations of less porous facies, such as shales, which accumulate mainly in more distal regions and structural lows. These authors also suggest that the coquinas reservoirs develop mainly along fault edges forming in beaches with bioclastic sediments therefore presenting greater interparticle pores which justifies the high porosity values.
deposição da formação lagoa feia. Boletim Técnico da Petrobras, Rio de Janeiro 28 (2), 91–101. Bertani, R.T., Carozzi, A.V., 1985. Lagoa Feia formation (lower cretaceous), Campos basin, offshore Brazil: rift valley stage lacustrine carbonate reservoirs — I. J. Pet. Geol. 8 (1), 37–58 htpps://doi.org/10.1111/j.1747-5457.1985.tb00190.x. Bruhn, C.H.L., Gomes, J.A.T., Lucchese, C.D., Johann, P.R.S., 2003. Campos Basin: Reservoir Characterization and Management – Historical Overview and Future Challenges. OTC 15220. Offshore Technology Conference, Houston, Texas, pp. 14. Bizotto, A.C., 2014. Coquinass Eoaptianas Do Sudoeste Da Bacia De Campos: Fácies Deposicionais, Eventos Diagenéticos e Fatores Controladores Da Qualidade Do Reservatório. Rio Claro –SP, pp. 155 Dissertação de Mestrado pela Universidade Estadual Paulista (UNESP) “Júlio de Mesquita Filho”. Bulhões, E.M., Amorin, W.N., 2005. Princípio da Sismo Camada Elementar e sua aplicação à Técnica Volume de Amplitudes (TecVA). Ninth International Congress of the Brazilian Geophysical Society. https://doi.org/10.1190/sbgf2005-275. Caers, J., 2005. Petroleum Geostatistics. Richardson, Society of Petroleum Engineers, pp. 88. Carvalho, M.D., Praça, U.M., Silva-Telles JR., A.C., Jahnert, R.J., Dias, J.L., 2000. Bioclastic carbonate lacustrine facies models in the Campos basin (lower cretaceous), Brazil. Bioclastic carbonate lacustrine facies models in the Campos basin (lower cretaceous), Brazil. In: In: Gierlowski-Kordesch, E.H., Kelts, K.R. (Eds.), Lake Basins through Space and Time: AAPG Studies in Geology, vol. 46. AAPG, Tulsa, Oklahoma, pp. 245–256. Castro, J.C., 2006. Evolução dos conhecimentos sobre as coquinass- reservatório da Formação Lagoa Feia no trend Badejo-Linguado-Pampo, Bacia de Campos. Geociencias 25 (2), 175–186. Castro, J.C., Azambuja Filho, N.C., 1981. Fácies, análise estratigráfica e reservatórios da Formação Lagoa Feia, Cretáceo Inferior da Bacia de Campos. pp. 110 PETROBRAS/ CENPES/LABOR, Relatório interno, CENPES-1.940. Guardado, L.R., Gamboa, L.A.P., Lucchesi, C.F., 1989. Petroleum geology of the Campos Basin, Brazil, a model for a producing Atlantic-type basin. In: Edwards, J.D., Santogrossi, P.A. (Eds.), Divergent/passive margin basins. American Association of Petroleum Geologist Memoir 48, pp. 3–79. https://doi.org/10.1306/M48508C1. Horschutz, P.M.C., Freitas, L.C.S., Stank, C.V., Barroso, A.S., Cruz, W.M., 1992. The Linguado, Carapeba, Vermelho, and Marimbá giant oil fields, Campos basin, offshore Brazil. In: In: Halbouty, M.T. (Ed.), Giant Oil and Gas Fields of the Decade 1978-1988, vol. 54. American Association of Petroleum Geologists Memoir, pp. 137–153. Karner, G.D., Gamboa, L.A.P., 2007. Timing and origin of the South Atlantic pre‐salt sag basins and their capping evaporites. In: In: Schereiber, B.C., Lugli, S., Babel, M. (Eds.), Evaporites through Space and Time, vol. 285. Geological Society, London, Special Publications, pp. 15–35. Lupinacci, W.M., Franco, A.P., Oliveira, S.A.M., Moraes, F.S., 2017. A combined timefrequency filtering strategy for Q-factor compensation of poststack seismic data. Geophysics 82 (1), V1–V6. https://doi.org/10.1190/geo2015-0470.1. Mello, M.R., 2008. The Super Giant Great Lagoa Feia Petroleum System: the New Frontier of Exploration in the Pre-salt Sequences of the Great Campos Basin, Brazilian. AAPG Search and Discovery Article. AAPG Annual Convention, San Antonio, Texas. Mohriak, W.U., Mello, M.R., Dewey, J.F., Maxwell, J.R., 1990. Petroleum geology of the Campos basin, offshore Brazil. In: Brooks, J. (Ed.), Classic Petroleum Provinces: Geological Society Special Publication 50. Geological Society, London, UK, pp. 119–141. Oliveira, V.C.B., Silva, M.A., C., Borghi, L.F., Carvalho, I.S., 2019. Lacustrine coquinas and hybrid deposits from rift phase: pre-Salt, lower cretaceous, Campos Basin, Brazil. J. South Am. Earth Sci. https://doi.org/10.1016/j.jsames.2019.102254. Pyrcz, M.J., Deutsch, C.V. (Eds.), 2014. Geostatistical Reservoir Modeling. Oxford University Press, New York, pp. 448. Russell, B., Hampson, D., 1991. Comparison of poststack seismic inversion methods. In: SEG Technical Program Expanded Abstracts 1991: Society of Exploration Geophysicists, pp. 876–878. https://doi.org/10.1190/1.1888870. Russell, B., Hampson, D., 2006. The old and the new in seismic inversion. 31. Canadian Society of Exploration Geophysics Recorder, pp. 5–10 10. Schaller, H., Terra, G.S., Cruz, C.E.S., Spadini, A.R., 1981. Estudo preliminar da Fm, Lagoa Feia, area de Badejo/Pampo, Bacia de Campos. Int. Rep., Rio de Janeiro, Petrobras, pp. 17. Tigre, C.A., Schaller, H., Del Lucchese JR., , Possato, S., 1983. Pampo, Linguado, and Badejo fields: their discoveries, appraisals, and early production systems. In: Offshore Technology Conference, Houston, Texas, OTC 4627. Thompson, D.L., Stilwell, J.D., Hall, M., 2015. Lacustrine carbonate reservoirs from early cretaceous rift lakes of western Gondwana: pre-salt coquinass of Brazil and west Africa. Gondwana Res. 28 (1), 26–51. https://doi.org/10.1016/j.gr.2014.12.005. Winter, W.R., Jahnert, R.J., França, A.B., 2007. Bacia de Campos. Bol. Geociencias Petrobras 15 (2), 511–529. Ziegel, E.R., Deutsch, C.V., Journel, A.G., 1998. Geostatistical software library and user's guide. Technometrics 40 (4), 357. https://doi.org/10.2307/1270548.
5. Conclusions The proposed workflow was efficient in the individualization of the coquinas levels in the Linguado Field, improving the understanding of the carbonate platform. Preconditioning and seismic inversion allowed the interpretation of the pre-Jiquiá unconformity, the top of the Lower Coquinas, the base of the Upper Coquinas and the pre-Alagoas unconformities. The acoustic impedance contrasts between the layers allowed discrimination of the high porosity coquinas facies with low impedance values from the low porosity finer sediments with high impedance values. The lower coquinas bank was characterized as the main exploratory target in the study area, due to its higher effective porosity, thickness and net to pay intervals, when compared to the upper coquinas bank which presented a greater heterogeneity and overall lower porosity. The geostatistical method also allowed to point areas with high effective porosity that were not drilled yet. The porosity model corroborated the acoustic impedance results. The geobody extraction provided a geological model of distribution for the more porous facies allowed the identification of an area with high porosity values not yet drilling. Finally, the presented methodology was efficient in the identification of new exploratory perspectives in hydrocarbon fields considered relatively mature, as in the present case of study. Acknowledgements The authors thank the Agência Nacional do Petróleo, Gás Natural e Biocombustíveis (ANP) for providing the seismic data used in this research, the Schlumberger for providing the Petrel Software, and the Compagnie Générale de Géophysique for providing the Hampson–Russell Software. The first author thanks the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) for financial support. The authors also acknowledge the Tiago Alves and the anonymous reviewer, whose suggestions contributed to the improvement of the text. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.petrol.2019.106451. References Azevedo, L., Soares, A., 2017. Geostatistical Methods for Reservoir Geophysics. Springer International Publishing, Advances in Oil and Gas Exploration & Production, Cham, pp. 159. https://doi.org/10.1007/978-3-319-53201-1. Baumgarten, C.S., 1985. Evolução estrutural de pampo, badejo e linguado durante a
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A workflow for reservoir characterization applied to presalt coquinas from the Linguado Field, Campos Basin, Brazil
T
Alessandra Alves Peçanhaa,∗, Wagner Moreira Lupinaccia,b, Danilo Jotta Ariza Ferreiraa,c, Antonio Fernando Menezes Freirea a
Universidade Federal Fluminense, Department of Geology and Geophysics (GIECAR), Av. General Tavares de Souza, Niterói, RJ, 24210-346, Brazil Universidade Federal Fluminense, Biomass and Water Management Research Center (NAB), R. Prof. Edmundo March, S/n, Boa Viagem, Niterói, RJ, 24210-330, Brazil c Schlumberger, Software Integrated Solutions, Av. República Do Chile 330, RJ, 20031-170, Brazil b
A R T I C LE I N FO
A B S T R A C T
Keywords: Reservoir characterization Presalt Geobody Porosity modeling Acoustic inversion Coquinas
Characterization of presalt coquinas reservoirs is a know challenging task due to its facies and, consequently, petrophysical properties heterogeneity and anisotropy. This fact makes the traditional seismic interpretation and well log analysis workflow not enough for the interpreter to address reasonably the reservoir complexity. In this study, a methodology integrating different geological and geophysical interpretation techniques based on data pre-conditioning, model-based seismic acoustic inversion, effective porosity geostatistical modeling using sequential gaussian simulation with collocated co-kriging and geobody interpretation is proposed to obtain maximum information from the available data which consists on post-stack seismic and well logs from the lacustrine coquinas carbonate reservoirs from the Coqueiros Formation located in the Linguado Field on Campos Basin. Acoustic seismic inversion results allowed the interpretation of four new seismic horizons that could individualize two coquinas intervals and effective porosity modeling results allowed the geobody extraction of the coquinas banks that represent the best reservoir facies within the study area with effective porosities between 13 and 30% making it even possible to identify new exploratory areas. Therefore, the proposed workflow is very reliable for coquinas reservoirs characterization and can be applied in other areas.
1. Introduction The Linguado Field is in the southwest region of Campos basin. It has four main reservoirs represented by sandstones from the Carapebus Formation, marine carbonates from the Quissamã Formation, lacustrine carbonates from the Coqueiros Formation and fractured basalts from the Cabiúnas Formation (Winter et al., 2007), also known as the economic basement which represents the limit in which below there are no longer rocks that are viable hydrocarbon reservoirs. The Coqueiros Formation, focus of this study, was deposited in a lacustrine setting during the Barremian to the beginning of the Aptian. Comprises intercalations of organic matter rich shales, Campos basin main source rock, and coquinas banks composed mainly of bivalve mollusk shells that represent the formation reservoirs. The coquinas rocks have been extensively studied by several authors over the years (Schaller et al., 1981; Bertani and Carozzi, 1985; Carvalho et al., 2000; Castro, 2006; Mello, 2008), however their characterization is still very challenging because of its unique faciological heterogeneity, anisotropy and
diagenetic evolution making it difficult to predict petrophysical properties distribution and, consequently infer reservoir quality (Bruhn et al., 2003; Thompson et al., 2015). In the Linguado Field, the coquinas sequences are composed by the sedimentation of grainstones, packstones, rudstones in coarsening upwards cycles, with average porosities between 15 and 20% and medium permeabilities varying from less than 1mD to more than 500mD with an average thickness of 100 m (Horschutz et al., 1992; Castro, 2006, Bernardes Oliveira et al., 2019). Coquinas intervals were divided by Schaller et al. (1981) into upper and lower banks that are usually separated by fine grained rocks such as shale, silt, and marl, and represent two distinct depositional stages. The lower coquinas interval presents thicknesses of 75 m–150 m composed by bioclastic deposits intercalated with thin layers of sandstone and shales constituting the main exploratory interval of the Linguado Field. As for the upper coquinas interval, it has lower porosity and thickness, 30 m in average, representing secondary reservoirs within the Coqueiros Formation (Tigre et al., 1983). The paleoenvironmental
∗
Corresponding author. E-mail addresses: [email protected] (A.A. Peçanha), [email protected]ff.br (W.M. Lupinacci), [email protected] (D.J.A. Ferreira), [email protected]ff.br (A.F.M. Freire). https://doi.org/10.1016/j.petrol.2019.106451 Received 13 May 2019; Received in revised form 29 July 2019; Accepted 28 August 2019 Available online 03 September 2019 0920-4105/ © 2019 Elsevier B.V. All rights reserved.
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Fig. 1. Location map of the wells and seismic data available for the study in the Linguado Field, Campos Basin. Also, IL = inline 1570 and AB = arbitrary seismic section position can be observed.
Fig. 2. Proposed workflow for the individualization and characterization of the coquinas banks.
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Fig. 3. Seismic section of inline 1570 a) uninterpreted and b) interpreted.
study. In the seismic interpretation stage, the economic basement top and evaporite sequence base, Retiro Formation, seismic unconformities (Winter et al., 2007) that delimit the stratigraphic interval in which coquinas are included within Linguado field were interpreted coupled with main rift phase faults to create a structural-stratigraphic model of the Lagoa Feia Group, that in the case of Linguado field is mainly composed by Coqueiros Formation. This model helped to understand the compartmentalization of the area and served as input for porosity modeling. The TecVa, amplitude volume technique, attribute was used as a tool to aid in the interpretation of seismic horizons and, especially, faults (Bulhões and Amorin, 2005). This seismic attribute transforms the amplitude into a pseudo relief, which helps in the visualization and mapping of horizons and faults. The seismic data preconditioning workflow applied to improve resolution and increase the signal-to-noise ratio, before performing seismic inversion and porosity modeling, was based on the work of Lupinacci et al. (2017) and consisted into three stages: curvelet filtering, inverse Q filtering, and band pass filter up to 60 Hz. Seismic well tie was performed in the interval of the Lagoa Feia Group. In this step, the base, economic basement, and top, evaporites base, horizons of the Lagoa Feia Group were used as input data along with markers, sonic and density well logs, checkshots and the preconditioned seismic data. The objective of this step was positioning of the wells in time with the seismic data trying to get the best correlation factor between synthetic and real seismic traces to be able to perform an optimum seismic inversion. After this stage, the acoustic impedance logs were filtered up to 10 Hz to be extrapolated to construct the initial acoustic impedance model for seismic inversion, which had as guides the top and base horizons of the Lagoa Feia Group. Well 1-RJS-74-RJ was removed from
evolution that define the two levels of coquinas transitions from alluvial fans to lacustrine deposits (Thompson et al., 2015). According to the Brazilian National Petroleum Agency, Linguado field together with three other adjacent fields in the region, Badejo, Trilha and Pampo, produces 16,000 bbl/day of oil and 5 mm3/day of natural gas from the Pampo-1, P-7, and P-12 platforms, which are connected to 45 production wells. In 1985, 1994, were registered the higher production peaks of oil and natural gas, respectively, thus the Linguado Field is considered a mature hydrocarbon field with production in decrease since then. Therefore, the aim of this study is to propose a workflow for the individualization and characterization of the two coquinas reservoir intervals in the Linguado Field to better address its complexity based on the seismic, well and rock sample data integration and to provide efficient tools for seismic interpretation, porosity modeling and geobody extraction of coquinas banks in the study area. Available data was composed of 13 wells data and 65 km2 of 3D post-stack seismic data within the field area (Fig. 1). 2. Methodology The proposed workflow for characterization of the coquinas banks carbonate reservoirs from the Coqueiros Formation was divided into five main stages: (1) study interval seismic interpretation and structural model and grid construction; (2) seismic data preconditioning to increase resolution and signal to noise ratio; (3) acoustic inversion using model-based inversion method (Russell and Hampson, 1991, 2006); (4) porosity modeling through sequential gaussian simulation geostatistical method with colocalized co-kriging using the acoustic impedance results (Pyrcz and Deutsch, 2014; Azevedo and Soares, 2017); (5) coquinas intervals geobody extraction, using as main criteria the porosity contrast of these facies. Fig. 2 resumes the workflow applied to this 3
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Fig. 4. (a) Map of the pre-evaporite unconformity with main faults, (top of the Lagoa Feia Group) and (b) 3D view of the basement and pre-evaporite unconformities (top and base of the Lagoa Feia Group) and faults constructed structural model for the area.
the construction of the initial model and inversion to be a quality control well for the seismic inversion results. Porosity modeling was then performed with the effective porosities, calculated in the wells, that were transformed to a gaussian distribution and, as the sample points, available well data, are sparse and irregular throughout the study area, and the construction of a gaussian variogram model was adjusted based on a great number of linear combinations tests for sample pairs in order to ideally describe the spatial correlation of sampled points coupled with geological conceptual models (Caers, 2005). After several trials, the direction NE-SW was defined as a direction of lowest variability, parallel to the regional rift fault directions of the Campos Basin, and the direction NW-SE as the direction of greatest variability and porosity modeling was performed through sequential gaussian simulation integrated with the colocalized co-kriging (Ziegel et al., 1998) using as secondary variable the acoustic impedance volume. Finally, a geobody was extracted from the porosity modeling volume that represents the facies of greater effective porosity, the
Table 1 Correlation factor of the well ties. Wells
Correlation Factor, %
1-RJS-74-RJ 1-RJS-49-RJ 3-LI-2-RJ 3-LI-4-RJS 3-LI-5-RJS 3-LI-8-RJS 3-RJS-157C-RJ 3-RJS-167-RJ 3-RJS-73B-RJ 4-RJS-139-RJ 4-RJS-156-RJ 7-LI-10 7-LI-3
71 77 72 56 76 78 85 63 72 75 79 85 77
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unconformity presents erosive truncation terminations with low to high positive amplitudes and lateral continuity depending on seismic quality. Below this reflector the seismic facies is chaotic. As for the reflector corresponding to the salt base unconformity, top of the Lagoa Feia Group, it is characterized by low to medium negative values of amplitude and fair lateral continuity. Seismic facies within the mapped interval are mostly plane parallel reflectors at the structural highs becoming more chaotic at the structural lows. The coquinas reservoirs were expected to be related to the plane parallel reflectors. A structural model and grid were generated after seismic interpretation and can be observed in Fig. 4a. The surfaces of this model show an apparent dip to the southeast towards the depocenter of Campos Basin (Fig. 4b). The two major rift faults, one in the eastern portion (AA’) and the other in the western portion (BB’), have N–S orientation and differ slightly from the usual NE-SW orientation for rift faults in Campos Basin. Faulting in the Linguado field are mostly normal faults with few antithetic associated. The largest fault localized in the east (AA’) divides the Lagoa Feia Group into a structural low to the east and a structural high to the west, with all wells located at the structural high. Seismic well tie within the Lagoa Feia Group interval was performed after the seismic data preconditioning and the correlation coefficients obtained for each well is shown in Table 1. The thirteen wells presented, in majority, correlation factors higher than 70%, a percentage considered acceptable for construction of the low frequency acoustic impedance model and the inversion itself. Also, the average of the wavelets estimated for the well tie process, except from 1-RJS-74-RJ quality control well, was created for posterior use for seismic inversion. Subsequently, seismic inversion was performed considering parametrization of number of algorithm interactions and acceptable acoustic impedance deviations values from the measured values from well logs. For quality control purposes, inversion results in the well locations are shown in Fig. 5 and a good correlation can be observed, in the interest interval, for the impedances of the well logs. For well 1-RJS74-RJ, used as a blind test, is also observed a good correlation between the original and inversion acoustic impedance values, which confirms that seismic inversion result is robust. The arbitrary section AB is shown in Fig. 6 to illustrate the acoustic impedance results and a division is clear within Lagoa Feia Group interval where the group upper portion presents medium to high acoustic impedance values and the lower part presents low to medium values. The aptian carbonate reservoirs, focus of this study, are represented mostly by the upper part of the Lagoa Feia Group. Therefore, the impedance contrasts and the chronostratigraphic markers of the wells allowed the identification and mapping of top and bottom of the upper and lower coquinas banks, as described in the literature by Schaller et al. (1981) and Baumgarten (1985), and the interpretation of two new seismic unconformities pre-Alagoas and pre-
Fig. 5. Comparison between the acoustic impedance (AI) logs (blue curve), the AI from the seismic inversion (red curve), and background AI model (black curve) at well locations. The interval of interest, Lagoa Feia Group, is limited by the yellow lines. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
coquinas banks, in the Coqueiros Formation. Cutoff points from 13% to 30% porosity were applied for the extraction. 3. Results Seismic interpretation results consisted in the mapping of the economic basement unconformity which separates the top of the Cabiúnas Formation from the base of the Lagoa Feia Group, the salt base unconformity which separates the base of the Retiro Formation from the top of the Lagoa Feia Group and main faulting. These interfaces are shown in seismic section of Fig. 3. The seismic reflector that corresponds to the economic basement
Fig. 6. Arbitrary section AB with acoustic impedance values, passing through wells 3-RJS-73B-RJ, 1-RJS-49-RJ and 3-LI-8-RJS. 5
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Fig. 7. Simplified chronostratigraphic chart of the Campos Basin focusing on the presalt interval.
Fig. 8. Acoustic impedance in inline 1570 with interpreted horizons.
The last mapped horizon is the top of the upper coquinas bank which also represents the top of the Coqueiros Formation, also known as the pre-Alagoas unconformity and the end of the rift phase. This horizon separates the coquinas sequence from the Macabu Formation (Winter et al., 2007), an interval where slightly higher acoustic impedance values are noted, ranging from 9000 to 11,000 m/s × g/cm3. Finally, the pre-evaporite unconformity is well marked by the start of higher acoustic impedance values above 11,000 m/s × g/cm3 and represents the beginning of the Retiro Formation evaporites. The acoustic impedance projected over the top of the lower coquinas bank is shown in Fig. 9a. This map view shows that, in general, the reservoir facies, where the wells were drilled, are regions with the lowest values of acoustic impedance. In Fig. 9b, the acoustic impedance is shown on the top of the upper coquinas banks and it can be noted that the wells were drilled in places where acoustic impedance values are slightly higher when compared to lower coquinas banks. The clay volume, effective porosity, water saturation and net to pay intervals were calculated using well logs and these results are shown for the wells 3-LI-2-RJS, 1-RJS-74-RJ and 1-RJS-49-RJ in Fig. 10. Based in the petrophysical evaluation, it was observed low clay content (low presence of marls, shales and mudstones) and high values of effective porosity in the lower coquinas level, where mean effective porosities are of 15%, and can reach maximum of 30%. This level presents a considerable thickness of reservoir rock, greater than 100 m in most of the wells analyzed (Fig. 10a) and it is also where the largest net to pay thicknesses are observed, as shown in well 1-RJS-49-RJ (Fig. 10c). In
Jiquiá (Winter et al., 2007). The base of Coqueiros Formation horizon represents the LF-35 stratigraphic marker from the wells which is the base of the lower coquinas bank identified in the literature as the limit between the lower siliciclastic talc-stevensite sequence and mixed siliciclastic-carbonate coquinas sequence (Mohriak et al., 1990; Karner and Gamboa, 2007). A simplified chronostratigraphic chart focusing on the presalt interval with its main unconformities is shown in Fig. 7. Fig. 8 shows all the seismic horizons interpreted using acoustic impedance results. In order to map the base of Coqueiros Formation horizon, it was observed a high contrast of acoustic impedance between the upper portion of the talc-stevensite sequence which presents medium acoustic impedance values (from 8000 to 10,000 m/s × g/cm3), compared to the basal portion of the coquinas sequence, which presents considerably lower acoustic impedance values (from 6000 to 8500 m/s × g/cm3). The pre-Jiquiá unconformity was mapped using as reference the upper limit of lower coquina bank that contrasts with higher acoustic impedance values above it. This seismic horizon divides the Coqueiros Formation into two distinct depositional phases, separated by the sedimentation of the Jiquiá shale (Horschutz et al., 1992) that presents high acoustic impedance values varying from 9000 to 14,000 m/s × g/ cm3. The base of the upper coquinas banks was also mapped, consequently, because of the contrast with the Jiquiá shale higher acoustic impedance values since it has lower impedance values, around 6000 and 8500 m/s × g/cm3, when compared to it. 6
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Fig. 9. Maps with acoustic impedance on the tops of the Lower Coquinas (a) and the Upper Coquinas (b).
coquinas bank does not constitute an important exploratory target due to the presence of many finer facies such as packstones and wackestones deposited in a moderate to low energy environment, that usually become a hydrocarbon flow barrier. After well logs evaluation, a structural model between the preJiquiá and pre-evaporite unconformities considering the mapped faults was constructed and then gridded with 10 layers for the porosity modeling. The effective porosity logs were used for the porosity modeling with the acoustic impedance volume as a secondary variable. The obtained results can be seen in Fig. 11 and presented an average effective porosity of 12.8%. The effective porosity over the top of the lower coquinas bank is
the lower coquinas level is reported a greater incidence of pure coquinas, rudstones and bioclastic grains, defined by Castro and Azambuja Filho (1981) which are the highest energy facies within Coqueiros Formation and represent the main reservoir for the study area. The upper coquinas bank has an average effective porosity of 12%, however in some wells the porosity is almost null, as is the case of well 1-RJS-74-RJ (Fig. 10b). The gross is considerably lower than that observed in the lower coquinas bank, not reaching values greater than 30 m. Also, it is more heterogeneous, presenting numerous intercalations with finer sediment rocks, which results in zones with lower permoporous characteristics. The net to pay intervals are thinner or even absent in some wells. According to Bizotto (2014), the upper
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Fig. 10. Logs evaluation in well 3-LI-2-RJS (a), 1RJS-74-RJ (b) and 1-RJS-49-RJ (c). Track 1: depth in meters; Track 2: Coqueiros Formation interval; Track 3: lithological log; Track 4: clay volume (VShale); Track 5: total porosity (PHIT) and effective porosity (PHIE); Track 6: water saturation (Sw); Track 6: net-pay intervals. Highlighting the coquinas levels: upper coquinas (green rectangle) and Lower Coquinas (blue rectangle). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 11. Porosity modeling results for the Coqueiros Formation using the Sequential Gaussian Simulation method with colocalized co-kriging.
sub commercial well, is in an area with relatively high porosity, but after petrophysical evaluation it was considered to be below oil water contact, which explains its non-commerciality. As for well 1-RJS-49-RJ, also classified as non-commercial, it is positioned on a location with low effective porosity. The porosity map on the upper coquinas level (Fig. 12b) also has
shown in Fig. 12a, and as can be observed several portions present very porous facies and, consequently almost all wells were drilled in regions with high porosity values. Even the wells 3-LI-8-RJS; 3-LI-2-RJS; 1-RJS49-RJ and 3-LI-4-RJS, which were not drilled in locations where effective porosities as high as the others, still have a reasonable porosity and are classified as producing wells. Well 1-RJS-74-RJ, identified as a 8
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Fig. 12. Porosity maps of the Lower Coquinas (a) and Upper Coquinas (b).
levels. Ratifying the acoustic impedance results, the effective porosity maps over the top of upper and lower coquinas banks show that there is a large concentration of wells in the central field part and few wells drilled at low porosities for both intervals but mostly in the upper coquinas portion. Most of the wells were drilled in regions with an average porosity of 12%, as can be seen in Fig. 12 but there are regions
porous facies values similar to those found in the lower coquinas level, but the regions with these facies are smaller and discontinuous than those observed in the lower bank. Well 1-RJS-74-RJ also indicates low porosity at this coquinas level. The fact that this well is non-producing is explained by the higher water saturation in the more porous regions, and low porosities in the other intervals, besides having a layer of small thickness, impacting low gross and low net to pay at both the coquinas 9
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sediment content. A zoning of the more porous regions was possible with the geobody, allowing the predictability of facies of high energy lake environment, which composed the main lacustrine reservoirs of the rift phase.
4. Discussion Some areas of greater porosity occur at the edge of the large fault AA’ in Fig. 4a, which indicates that the sin-depositional tectonism may have been the mechanism responsible for the high porosities favoring the access of meteoric water in those regions causing dissolution and increasing interparticle spaces. In Fig. 12a, the lower coquinas bank presents an area with few wells drilled near of this fault, with high porosity values. This fact may be because even though this region have good reservoir rock characteristics, it is possible that due to the presence of faulting, active tectonism may have prevented the formation of a seal. The vertical heterogeneity observed in the Coqueiros Formation is the result of several depositional shallowing upward cycles which composed the two coquinas levels reflecting the continuous increase of energy in the depositional environment, culminating in the deposition of coquinas at the top of each phase (Bizotto, 2014). Fig. 14 shows the well correlation for wells 3-LI-02-RJS, 1-RJS-74RJ, 3-RJS-73B-RJ and 1-RJS-49-RJ. Along the Coqueiros Formation, the reduction of coarse-grained clastic sediments, such as sandstone and conglomerate, and the increase of marl and shale intercalations is observed from wells 3-LI-02-RJS to 1- RJS-49-RJ. This may indicate that since well 3-LI-02-RJS was drilled near a fault edge, contemporary tectonism to sedimentation caused more clastic sediments to occurs whereas, in well 1- RJS-49-RJ, there was a higher water column and lower tectonic activity during the sedimentation that made it possible for the coquinas sequences deposition. When comparing the depositional model suggested by Guardado et al. (1989), for lacustrine carbonates of the Coqueiros Formation, the
Fig. 13. Geobody extracted from the porosity model cutoffs where green colors represent porosities between 13% and 30% and yellow to red colors represent porosities between 30% and 35%. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
with effective porosities up to 20%–30%, which do not yet have drilled wells. Finally, a geobody was extracted based on the effective porosity values obtained from the geostatistical modeling (Fig. 13) using the cutoff range of 13%–30%. This geological body was constructed to individualize the most porous facies, especially the coquinas banks associated with high values of porosity. According to the evaluation of the logs, marl, shale, silt, mudstones and wackestones facies are the ones that have the lowest effective porosity, mainly due to high finer
Fig. 14. Correlation of wells 3-LI-2-RJS, 1-RJS-74-RJ, 3-RJS-73B-RJ and 1-RJS-49-RJ, with emphasis on the Coqueiros Formation lower coquinas (C.I) and upper coquinas (C.S) banks. 10
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geobody very closely resembles the carbonate banks of isolated coquinas over basement structural highs. Also, as described by Carvalho et al. (2000), these carbonate banks have aggradational deposition and lateral facies transition to finer facies and with low effective porosity, such as shale and silt. The regions absent in the geobody represent more abundant accumulations of less porous facies, such as shales, which accumulate mainly in more distal regions and structural lows. These authors also suggest that the coquinas reservoirs develop mainly along fault edges forming in beaches with bioclastic sediments therefore presenting greater interparticle pores which justifies the high porosity values.
deposição da formação lagoa feia. Boletim Técnico da Petrobras, Rio de Janeiro 28 (2), 91–101. Bertani, R.T., Carozzi, A.V., 1985. Lagoa Feia formation (lower cretaceous), Campos basin, offshore Brazil: rift valley stage lacustrine carbonate reservoirs — I. J. Pet. Geol. 8 (1), 37–58 htpps://doi.org/10.1111/j.1747-5457.1985.tb00190.x. Bruhn, C.H.L., Gomes, J.A.T., Lucchese, C.D., Johann, P.R.S., 2003. Campos Basin: Reservoir Characterization and Management – Historical Overview and Future Challenges. OTC 15220. Offshore Technology Conference, Houston, Texas, pp. 14. Bizotto, A.C., 2014. Coquinass Eoaptianas Do Sudoeste Da Bacia De Campos: Fácies Deposicionais, Eventos Diagenéticos e Fatores Controladores Da Qualidade Do Reservatório. Rio Claro –SP, pp. 155 Dissertação de Mestrado pela Universidade Estadual Paulista (UNESP) “Júlio de Mesquita Filho”. Bulhões, E.M., Amorin, W.N., 2005. Princípio da Sismo Camada Elementar e sua aplicação à Técnica Volume de Amplitudes (TecVA). Ninth International Congress of the Brazilian Geophysical Society. https://doi.org/10.1190/sbgf2005-275. Caers, J., 2005. Petroleum Geostatistics. Richardson, Society of Petroleum Engineers, pp. 88. Carvalho, M.D., Praça, U.M., Silva-Telles JR., A.C., Jahnert, R.J., Dias, J.L., 2000. Bioclastic carbonate lacustrine facies models in the Campos basin (lower cretaceous), Brazil. Bioclastic carbonate lacustrine facies models in the Campos basin (lower cretaceous), Brazil. In: In: Gierlowski-Kordesch, E.H., Kelts, K.R. (Eds.), Lake Basins through Space and Time: AAPG Studies in Geology, vol. 46. AAPG, Tulsa, Oklahoma, pp. 245–256. Castro, J.C., 2006. Evolução dos conhecimentos sobre as coquinass- reservatório da Formação Lagoa Feia no trend Badejo-Linguado-Pampo, Bacia de Campos. Geociencias 25 (2), 175–186. Castro, J.C., Azambuja Filho, N.C., 1981. Fácies, análise estratigráfica e reservatórios da Formação Lagoa Feia, Cretáceo Inferior da Bacia de Campos. pp. 110 PETROBRAS/ CENPES/LABOR, Relatório interno, CENPES-1.940. Guardado, L.R., Gamboa, L.A.P., Lucchesi, C.F., 1989. Petroleum geology of the Campos Basin, Brazil, a model for a producing Atlantic-type basin. In: Edwards, J.D., Santogrossi, P.A. (Eds.), Divergent/passive margin basins. American Association of Petroleum Geologist Memoir 48, pp. 3–79. https://doi.org/10.1306/M48508C1. Horschutz, P.M.C., Freitas, L.C.S., Stank, C.V., Barroso, A.S., Cruz, W.M., 1992. The Linguado, Carapeba, Vermelho, and Marimbá giant oil fields, Campos basin, offshore Brazil. In: In: Halbouty, M.T. (Ed.), Giant Oil and Gas Fields of the Decade 1978-1988, vol. 54. American Association of Petroleum Geologists Memoir, pp. 137–153. Karner, G.D., Gamboa, L.A.P., 2007. Timing and origin of the South Atlantic pre‐salt sag basins and their capping evaporites. In: In: Schereiber, B.C., Lugli, S., Babel, M. (Eds.), Evaporites through Space and Time, vol. 285. Geological Society, London, Special Publications, pp. 15–35. Lupinacci, W.M., Franco, A.P., Oliveira, S.A.M., Moraes, F.S., 2017. A combined timefrequency filtering strategy for Q-factor compensation of poststack seismic data. Geophysics 82 (1), V1–V6. https://doi.org/10.1190/geo2015-0470.1. Mello, M.R., 2008. The Super Giant Great Lagoa Feia Petroleum System: the New Frontier of Exploration in the Pre-salt Sequences of the Great Campos Basin, Brazilian. AAPG Search and Discovery Article. AAPG Annual Convention, San Antonio, Texas. Mohriak, W.U., Mello, M.R., Dewey, J.F., Maxwell, J.R., 1990. Petroleum geology of the Campos basin, offshore Brazil. In: Brooks, J. (Ed.), Classic Petroleum Provinces: Geological Society Special Publication 50. Geological Society, London, UK, pp. 119–141. Oliveira, V.C.B., Silva, M.A., C., Borghi, L.F., Carvalho, I.S., 2019. Lacustrine coquinas and hybrid deposits from rift phase: pre-Salt, lower cretaceous, Campos Basin, Brazil. J. South Am. Earth Sci. https://doi.org/10.1016/j.jsames.2019.102254. Pyrcz, M.J., Deutsch, C.V. (Eds.), 2014. Geostatistical Reservoir Modeling. Oxford University Press, New York, pp. 448. Russell, B., Hampson, D., 1991. Comparison of poststack seismic inversion methods. In: SEG Technical Program Expanded Abstracts 1991: Society of Exploration Geophysicists, pp. 876–878. https://doi.org/10.1190/1.1888870. Russell, B., Hampson, D., 2006. The old and the new in seismic inversion. 31. Canadian Society of Exploration Geophysics Recorder, pp. 5–10 10. Schaller, H., Terra, G.S., Cruz, C.E.S., Spadini, A.R., 1981. Estudo preliminar da Fm, Lagoa Feia, area de Badejo/Pampo, Bacia de Campos. Int. Rep., Rio de Janeiro, Petrobras, pp. 17. Tigre, C.A., Schaller, H., Del Lucchese JR., , Possato, S., 1983. Pampo, Linguado, and Badejo fields: their discoveries, appraisals, and early production systems. In: Offshore Technology Conference, Houston, Texas, OTC 4627. Thompson, D.L., Stilwell, J.D., Hall, M., 2015. Lacustrine carbonate reservoirs from early cretaceous rift lakes of western Gondwana: pre-salt coquinass of Brazil and west Africa. Gondwana Res. 28 (1), 26–51. https://doi.org/10.1016/j.gr.2014.12.005. Winter, W.R., Jahnert, R.J., França, A.B., 2007. Bacia de Campos. Bol. Geociencias Petrobras 15 (2), 511–529. Ziegel, E.R., Deutsch, C.V., Journel, A.G., 1998. Geostatistical software library and user's guide. Technometrics 40 (4), 357. https://doi.org/10.2307/1270548.
5. Conclusions The proposed workflow was efficient in the individualization of the coquinas levels in the Linguado Field, improving the understanding of the carbonate platform. Preconditioning and seismic inversion allowed the interpretation of the pre-Jiquiá unconformity, the top of the Lower Coquinas, the base of the Upper Coquinas and the pre-Alagoas unconformities. The acoustic impedance contrasts between the layers allowed discrimination of the high porosity coquinas facies with low impedance values from the low porosity finer sediments with high impedance values. The lower coquinas bank was characterized as the main exploratory target in the study area, due to its higher effective porosity, thickness and net to pay intervals, when compared to the upper coquinas bank which presented a greater heterogeneity and overall lower porosity. The geostatistical method also allowed to point areas with high effective porosity that were not drilled yet. The porosity model corroborated the acoustic impedance results. The geobody extraction provided a geological model of distribution for the more porous facies allowed the identification of an area with high porosity values not yet drilling. Finally, the presented methodology was efficient in the identification of new exploratory perspectives in hydrocarbon fields considered relatively mature, as in the present case of study. Acknowledgements The authors thank the Agência Nacional do Petróleo, Gás Natural e Biocombustíveis (ANP) for providing the seismic data used in this research, the Schlumberger for providing the Petrel Software, and the Compagnie Générale de Géophysique for providing the Hampson–Russell Software. The first author thanks the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) for financial support. The authors also acknowledge the Tiago Alves and the anonymous reviewer, whose suggestions contributed to the improvement of the text. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.petrol.2019.106451. References Azevedo, L., Soares, A., 2017. Geostatistical Methods for Reservoir Geophysics. Springer International Publishing, Advances in Oil and Gas Exploration & Production, Cham, pp. 159. https://doi.org/10.1007/978-3-319-53201-1. Baumgarten, C.S., 1985. Evolução estrutural de pampo, badejo e linguado durante a
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