Abstract:
Carbonate mounds, as described herein, often present seismic characteristics such as low amplitude and a high density of faults and fractures, which can easily be oversampled and blur other rock features in simple geobody extraction processes. We have developed a workflow for combining geometric attributes and hybrid spectral decomposition (HSD) to efficiently identify good-quality reservoirs in carbonate mounds within the complex environment of the Brazilian presalt zone. To better identify these reservoirs within the seismic volume of carbonate mounds, we divide our methodology into four stages: seismic data acquisition and processing overview, preconditioning of seismic data using structural-oriented filtering and imaging enhancement, calculation of seismic attributes, and classification of seismic facies. Although coherence and curvature attributes are often used to identify high-density fault and fracture zones, representing one of the most important features of carbonate mounds, HSD is necessary to discriminate low-amplitude carbonate mounds (good reservoir quality) from low-amplitude clay zones (nonreservoir). Finally, we use a multiattribute facies classification to generate a geologically significant outcome and to guide a final geobody extraction that is calibrated by well data and that can be used as a spatial indicator of the distribution of good reservoir quality for static modeling. Introduction Brazil has been producing oil from presalt carbonate reservoirs over the past decade. Recently, these reservoirs attained an incredible output of just more than 1.7 million barrels of oil equivalent per day, representing more than half of the country’s daily production and demonstrating the importance of these carbonate reservoirs to Brazil. However, it is tremendously challenging to map and characterize these carbonate reservoirs given their considerable spatial heterogeneity, complex pore systems, and often ambiguous seismic responses. Burgess et al. (2013) define criteria for discriminating different carbonate features in a seismic image that involve: regional constraints, analysis of basic seismic geometries, and analyses of geophysical details and finer scale seismic geometries. For the purpose of this work, we adopted analyses of seismic geometries and geophysical details, as well as amplitude anomalies and the behavior of frequencies in the reservoir interval, together with the high density of faults and fractures, to define carbonate features, many of which were assessed at a subseismic scale (Wright and Rodriguez, 2018). Here, we propose a workflow for identifying and characterizing carbonate mounds in the Brazilian presalt zone using a combination of hybrid spectral decomposition (HSD) together with geometric attributes and curvature and coherence attributes. For this work, we use the term carbonate mounds to describe almost conical carbonate bodies of pronounced relief that are often difficult to map seismically due to their ambiguous limits and internal low-amplitude reflectors, but that exhibit excellent reservoir quality in terms of matrix and associated fracturing and that have been successfully drilled, evaluated, and tested. It is beyond the scope of this work to interpret these features further or to establish their depositional environment. For a broader perception of the many interpretations of these presalt carbonates we suggest, amongst others, the works of Wright and Barnett (2017) on Barra Velha Formation depositional systems, Buckley et al. (2015) on early Cretaceous lacustrine carbonate platforms, Wright and Barnett (2017) on depositional models for the presalt Barra Velha Formation, and Wright and Rodriguez (2018) on depositional interpretations of presalt environments and their links to seismic facies. Our Petrogal Brasil S.A., Rio de Janeiro, Brazil and Universidade Federal Fluminense, Niteroi, Brazil. E-mail: carlosfzk@gmail.com. Petrogal Brasil S.A., Rio de Janeiro, Brazil. E-mail: mariaolhoazul@petrogalbrasil.com. Universidade Federal Fluminense, Niteroi, Brazil. E-mail: wagnerlupinacci@id.uff.br. Emerson Automation Solutions, Rio de Janeiro, Brazil. E-mail: leandro.machado@emerson.com. Manuscript received by the Editor 3 January 2018; revised manuscript received 10 November 2018; published ahead of production 08 February 2019; published online 01 April 2019. This paper appears in Interpretation, Vol. 7, No. 2 (May 2019); p. T467–T476, 12 FIGS., 2 TABLES. http://dx.doi.org/10.1190/INT-2018-0004.1. © 2019 Society of Exploration Geophysicists and American Association of Petroleum Geologists. All rights reserved. t Technical papers Interpretation / May 2019 T467 D ow nl oa de d 04 /0 3/ 19 R ed is tr ib ut io n su bj ec t t o SE G li ce ns e or c op yr ig ht ; s ee T er m s of U se a t h ttp :// lib ra ry .s eg .o rg / workflow is focused on characterizing seismic facies and their relationship to present-day reservoir quality, which we believe can be applied and adjusted to different settings within the Brazilian presalt sequence. Our intent is to detail a workflow that can facilitate mapping of present-day good reservoir quality carbonate mound geometries to enable their characterization from a seismic perspective and to allow assessment of their spatial distribution for the purposes of reservoir modeling during the exploration and appraisal stages. Seismic attenuation can greatly affect the quality of seismic signals perpetuated at considerable depths (Lupinacci and Oliveira, 2015; Yuan et al., 2017). Consequently, mapping carbonate mounds in the Brazilian presalt fields, which lie at depths ranging between 5000 and 6000 m and below an approximately 2000 m thick layer of salt, is a major challenge for geoscientists because of low seismic illumination and low-amplitude anomalies, low impedance, and the high fault and fracture density that are characteristic of these geologic features. It is difficult to identify and delineate such features in these presalt fields using only seismic data because of the complexity of the seismic image generated and the absence of impedance contrast between the reservoir and adjacent sealing facies (Zheng et al., 2007). Despite many criteria for presalt seismic data having already been defined, we consider in this study that general information about the acquisition and processing of such data is essential to understanding its ambiguities and limitations. Furthermore, because seismic data can be contaminated by random and coherent noise arising from data acquisition or complex geology that can bias results even after data processing and migration (Chopra and Marfurt, 2007), data preconditioning is crucial to obtain good results (Lupinacci et al., 2017). With respect to carbonate reservoir characterization, seismic facies analysis is increasingly seen as an effective way of estimating reservoir properties (Matos et al., 2007), combining different seismic attributes through pattern recognition algorithms, such as seismic multiattributes analysis (Rongchang et al., 2017) to identify, for example, lateral changes in a reservoir. Seismic attributes are important tools for reservoir characterization that can help to visually enhance or quantify features of interest (Chopra and Marfurt, 2007). However, selection of seismic attributes for analysis should be made with caution so as not to propagate false interpretations. Curvature and coherence attributes can be used together in seismic multiattribute analyses to increase the reliability of this type of geologic analysis. The curvature attribute describes how bent a curve is at a point along its length (Roberts, 2001), focusing on changes in shape. This attribute is a good predictor of faults, as well as anticline and syncline structures (Klein et al., 2008) because it is not affected by variations in amplitude related to changes in lithology and fluid. The coherence cube attribute — a measure of the similarity between neighboring seismic traces in three dimensions — has been used since 1995 (Bahorich and Farmer, 1995) as a powerful seismic interpretation tool for imaging geologic discontinuities, such as faults and fractures, which are recurrently associated with carbonate mound features in this study area. However, many ways of calculating coherence can be implemented. Here, we applied the eigenvalue-coherence algorithm (Gersztenkorn and Marfurt, 1999; Marfurt et al., 1999), which uses several adjacent traces within a local window to estimate discontinuity for each sample. Spectral decomposition is another widely used attribute for identifying seismic patterns. It can represent the seismic trace in a frequency domain or in subbands of frequencies. It can be used to identify subtle thickness variations and discontinuities, as well as to predict bedding thicknesses (e.g., Partyka et al., 1999). Spectral decomposition can also be used to identify low-frequency shadow, which may indicate the presence of hydrocarbons (Sun et al., 2002; Wang, 2007) or as in this study, to identify good quality reservoirs upon calibration by the well-log porosity response. Additionally, a frequency bandwidth related to seismic facies can be selected from a spectral decomposition analysis, so a specific amplitude range can be isolated that represents a reservoir anomaly (called HSD) (Jesus et al., 2017). Pattern recognition and classification of seismic features is fundamental to seismic data interpretation (Zhao et al., 2015), so uniting different criteria through several seismic attributes and establishing seismic facies classes is an excellent approach for isolating reservoirs of good quality in presalt carbonate mounds from shale or tight zones (nonreservoir). We propose a workflow for identifying and characterizing carbonate mounds in the Brazilian presalt zone using a combination of HSD with curvature and coherence geometric attributes. We chose those attributes because of their ability to provide useful geologic inform
