Mapping of pre-salt carbonate geobodies distribution and its relationship with stratigraphic and diagenetic evolution

• Grant number: 24/10663-1
• Support Opportunities: Scholarships in Brazil - Doctorate
• Start date: September 01, 2024
• End date: August 31, 2028
• Field of knowledge: Physical Sciences and Mathematics - Geosciences - Geology
• Agreement: Equinor (former Statoil)
• Principal Investigator: Alexandre Campane Vidal
• Grantee: Pietro Demattê Avona
• Host Institution: Centro de Estudos de Energia e Petróleo (CEPETRO). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Company: Universidade Estadual de Campinas (UNICAMP). Faculdade de Engenharia Mecânica (FEM)
• Associated research grant: 17/15736-3 - Engineering Research Centre in Reservoir and Production Management, AP.PCPE

Abstract

The Brazilian pre-salt reservoir was responsible for more than 70% of the nationalproduction in 2022 (The Brazilian National Agency of Petroleum, Natural Gas and Biofuels).Many pre-salt fields are under development and new discovery areas are still taking place. Duringthe exploration phase of the field, seismic data is the first available information for geologicalinterpretations to guide the exploratory drilling planning. In the development and productionphase of the field, the seismic data remains an important tool to improve the understanding ofreservoirs and to monitor the effects of production and water and gas injection (4D seismic). Toestablish reliable geological and reservoir models is necessary to understand the depositionalfacies and lithofacies distribution in the basin and for this, the seismic interpretation tied with wellinformation is one of the steps for reservoir characterization. Based on this, several types ofgeological information can be extracted from seismic data through the analysis of seismicattributes, which can be linked to geobodies of a given rock property (BABAK and LIU, 2018;SHI; XINMING; FOMEL, 2021).The use of multi-attribute analysis combined with neural network approach to distinguishsignal anomalies and detect seismic facies was proposed by COLPAERT et al. (2007). Thisworkflow was capable of distinguishing a diverse set of seismic units which are tied with wellsto improve the understanding of carbonate geometry and its distribution in space and time. In theBrazilian pre-salt play, ALVARENGA et al. (2022) applied a workflow to highlight the geobodiesof Coqueiros Formation in Campos Basin. Through the use of seismic attribute analysis, it waspossible to enhance the continuity of reflectors and obtain a better quality of seismic facies, whichtied to well logs can improve good reservoir zones mapping.This project proposes the development of methods and workflows that take into accountthe use of seismic attributes and machine learning algorithms to highlight carbonate geobodies inpre-salt reservoirs. It is expected that the combination of well log and seismic dataset will improve (AU)