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Fracture diagnostics using low frequency electromagnetic induction

Currently microseismic monitoring is widely used for fracture diagnosis. Since the method monitors the propagation of shear failure events, it is an indirect measure of the propped fracture geometry. Our primary interest is in estimating the orientation and length of the ‘propped’ fractures (not the created fractures), as that is the primary driver for well productivity. This thesis presents a new Low Frequency Electromagnetic Induction (LFEI) method that has the potential to estimate the propped length, height, orientation of hydraulic fractures, and vertical distribution of proppant within the fracture. The proposed technique involves pumping electrically conductive proppant (which is currently available) into the fracture and then using a specially built logging tool to measure the electromagnetic response of the formation. Results are presented for a proposed logging tool that consists of three sets of tri-directional transmitters and receivers at 6, 30 and 60 feet spacing respectively. The solution of Maxwell’s equations shows that it is possible to use the tool to determine both the orientation and the length of the fracture by detecting the location of these particles in the formation after hydraulic fracturing. Results for extensive sensitivity analysis are presented in this thesis to show the effect of different propped lengths, height and orientation of planar fractures in a shale environment. Multiple numerical simulations, using a state-of-the-art electromagnetic simulator (FEKO) indicate, as this work show, that we can detect and map fractures up to 250 feet in length, 0.2 inches wide, and with a 0 to 45 degree of inclination with respect to the wellbore. Special cases such as proppant banking, non-symmetrical bi-wing fractures, and wells with steel casing in place were studied. / text

Identiferoai:union.ndltd.org:UTEXAS/oai:repositories.lib.utexas.edu:2152/26443
Date10 October 2014
CreatorsBasu, Saptaswa
Source SetsUniversity of Texas
LanguageEnglish
Detected LanguageEnglish
TypeThesis
Formatapplication/pdf

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