--> Analysis of Potential Uncertainties in Opening-Mode Fractures Characterization Through the Scanline Technique of Aptian Carbonates, Araripe Basin, Northeast

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Analysis of Potential Uncertainties in Opening-Mode Fractures Characterization Through the Scanline Technique of Aptian Carbonates, Araripe Basin, Northeast

Rafael Santos1, Tiago Miranda2, Antonio Barbosa2, Igor Gomes1, Gabriel Matos3, Virginio Neumann2, Leonardo Nascimento Guimaraes1 and Julia Gale4

1Civil Engineering, Federal University of Pernambuco, Recife, Pernambuco, Brazil
2Geology, Federal University of Pernambuco, Recife, Pernambuco, Brazil
3CENPES, Petrobras, Rio de Janeiro, Rio de Janeiro, Brazil
4University of Texas, Austin, Texas, United States

June 3, 2015 Wednesday 8:30 A.M. AAPG Annual Convention and Exhibition, Denver, CO.

Abstract

The exploitation of hydrocarbon reserves in naturally fractured reservoirs has drawn considerable attention from the fracture characterization research community due to the importance of fractures in the prediction of fluid flow. Fractures can affect the flow and storage of valuable natural resources. One of the most common methods for rapidly analyzing fracture features is the scanline technique, which generates an approximately quantitative prediction of fracture density and frequency. This method aims to measure the main fracture attributes, such as fracture spacing and aperture. Despite the confidence provided by the systematic use of this method, errors and uncertainties caused by sampling biases exist. The problems caused by these uncertainties can negatively affect the construction of a computational model due to misleading trends. Using Monte Carlo simulations, this study evaluated the uncertainty caused by sampling biases in the scanline data of opening-mode fractures in outcrops of naturally fractured Aptian laminated limestone from the Crato Formation, Araripe Basin, northeastern Brazil. Currently this unit is studied as an analogue of Pre-Salt carbonate reservoir, Santos Basin, Brazil. In this study, errors and uncertainties were grouped into one parameter, termed the coefficient of uncertainty (CU) and defined as the ratio between the errors and uncertainties and the scanline data. We assumed a CU of 30% for measurements of fracture spacing and aperture, which were simulated separately and simultaneously. Thus, the propagation of errors and uncertainties in the scanline data to the coefficients of the corresponding power law was determined. Finally, the proposed statistical analysis of fracture attributes, principally for fracture aperture, showed that the uncertainties can significantly affect the power-law scaling.

AAPG Datapages/Search and Discovery Article #90216 ©2015 AAPG Annual Convention and Exhibition, Denver, CO., May 31 - June 3, 2015