First Break - Volume 27, Issue 5, 2009

Aristofanis Stefatos, Mikhail Boulaenko, and Jonny Hesthammer, provide what is probably the most realistic assessment to date of the potential exploration applications for the marine controlled source electromagnetic survey method, supported by statistical data from around the world.

One of the hottest trends in geophysical exploration today is the integration of data from multiple sources to produce a geologically consistent, quantitative interpretation of seafloor rock and fluid properties. In this case study Peter Harris, Zhijun Du, Lucy MacGregor, Wiebke Olsen, Rone Shu and Richard Cooper present the application of a practical integration workflow to seismic, controlled source electromagnetic (CSEM), and well log data from the Luva gas field, offshore Norway.

Sergio L. Fontes, Patricia P. de Lugao, Max A. Meju, Vinicius R. Pinto, Jean- Marie Flexor, Emin U. Ulugergerli, Emanuele F. La Terra, Luis A. Gallardo and Luiz Rijo present the first large-scale MMT survey acquired recently in Brazil by WesternGeco Electromagnetics in cooperation with Observatório Nacional/MCT and Petrobras as part of a major project on improving depth imaging by integrating multiple geophysical measurements in the Santos Basin.

Terje Holten, Eirik Grude Flekkøy,Bension Singer, Erik Mårten Blixt, Alfred Hanssen and Knut Jørgen Måløy outline an electromagnetic method for detection of hydrocarbons offshore which differs in some notable respects from the currently established marine controlled source EM technology.

Andrea Lovatini, Ken Umbach and Steve Patmore describe a promising application of the controlled source electromagnetic method which may have implications for future Arctic exploration.

Ian Somerton, Simon Campbell and Matthew Stewart describe how global databases of gravity and magnetic data provide the means to enhance geological understanding of the structural framework of most regions of the world.

The productivity of porous and fractured reservoir rocks depends heavily on the total permeability of the reservoir. Here we distinguish between matrix permeability, fracture permeability, and a ‘boundary permeability’ controlling pore fluid exchange between fractures and matrix pores. Seismic data are capable of tracking variations of the second and third types of permeability: fracture permeability is indicated by mapping fracture swarms; and boundary permeability is indicated by the dynamic properties of P-waves. To implement these capabilities, two groups of seismic attributes are proposed here. The group of attributes for mapping fracture swarms is traditional, whereas the group of attributes responding to variations of the boundary permeability has only been introduced recently. Permeability substitution modelling is done before using attributes of the second group. Application to an oil field with a tight, fractured carbonate reservoir in the Timan-Pechora province, Russia, enabled us to group the fracture-controlling faults into three categories having distinct multi-attribute patterns and diverse transport properties defined by specific combinations of fracture and boundary permeabilities.

Thin-bed reflectivity inversion is a form of spectral inversion which produces sparse reflectivity estimates. It resolves thin layers below the tuning thickness under favourable circumstances when the assumptions are met in practice. The process differs from other inversions in that it is driven by geological rather than mathematical assumptions, and is based on aspects of the local frequency spectrum obtained by using spectral decomposition. Application of thin-bed reflectivity inversion to seismic data yields superior resolution which can help in various ways. The advantages include being able to pick up more reflection detail, to perform more accurate interpretation on seismic volumes obtained by convolving reflectivity volumes with wavelets of higher bandwidth than the input data, and to visualize subtle anomalies when some attributes are run on thin-bed reflectivity inversion output. Thin-bed reflectivity inversion is a useful process which should be utilized for extracting meaningful information from surface seismic data in the characterization of thin reservoirs.