• Energy Research

O presente capítulo faz uma introdução geral sobre o tema hidratos de gás naturais, i.e., que ocorrem nos sedimentos, apresentando os tipos existentes, como se formam, os principais gases envolvidos, a sua importância econômica e ambiental (incluindo mudança climática e como geohazards), além de suas ocorrências naturais no mundo. A seguir é apresentado um breve histórico dos estudos e da exploração de hidratos de gás no Brasil, seguido de uma descrição das ocorrências naturais confirmadas no país, no leque do Amazonas (Bacia da Foz do Amazonas) e no Cone de Rio Grande (Bacia de Pelotas). Por fim é apresentada uma breve comparação entre as duas ocorrências e uma discussão sobre o desenvolvimento futuro da exploração de hidratos de gás no país. This chapter starts with an introduction of the topic of natural gas hydrates, presenting the main existing types, how they form, the main gases involved in their formation, their economic and environmental (including climate change and as geohazards) importance, in addition to their worldwide natural occurrences. Also included is a brief history of the study and exploration of gas hydrates in Brazil, and a description of the two confirmed occurrences in the country: The Amazon fan (Foz do Amazonas basin) and the Rio Grande Cone (Pelotas Basin). The chapter ends with a brief comparison between the two occurrences and a discussion about the future development of the exploration for gas hydrates in the country. National audience

The CSEM method, which is frequently used as a risk-reduction tool in hydrocarbon exploration, is finally moving to a new frontier: reservoir monitoring and surveillance. In the present work, we present a CSEM time-lapse interpretation workflow. One essential aspect of our workflow is the demonstration of the linear relationship between the anomalous transverse resistance, an attribute extracted from CSEM data inversion, and the SoPhiH attribute, which is estimated from fluid-flow simulators. Consequently, it is possible to reliably estimate SoPhiH maps from CSEM time-lapse surveys using such a relationship. We demonstrate our workflow’s effectiveness in the mature Marlim oilfield by simulating the CSEM time-lapse response after 30 and 40 years of seawater injection and detecting the remaining sweet spots in the reservoir. The Marlim reservoirs are analogous to several turbidite reservoirs worldwide, which can also be appraised with the proposed workflow. The prediction of SoPhiH maps by using CSEM data inversion can significantly improve reservoir time-lapse characterization.