Petrophysical Sensitivity of Elastic Modulus and Inverse Quality Factor (1/Q) Analysis in Well Logs,

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Date

2014

Journal Title

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Publisher

Akamai University Hawaii, USA

Abstract

Theoretical studies and laboratory experiments have shown that seismic attenuation (or inverse quality factor, 1/Q) is sensitive to the presence of fluids, degree of saturation, porosity, fault/fracture, and pressure in porous elastically heterogeneous rocks. However, the probable use of attenuation for reservoir characterization is yet to be tested using well log data. This paper applies the theories of modulus- frequency dispersion to test, theoretically, the sensitivity of P- and S-wave attenuation to the presence of fluids in porous rocks saturated with two or more fluids. Application of the attenuation theory to the analysis of P-wave and S-wave inverse quality factor ( and) in well log data shows that P-wave inverse quality factor is generally higher in hydrocarbon saturated rocks than in brine/water saturated rocks, while the S-wave inverse quality factor does not show direct sensitivity to fluid. A cross plot of the ratio of P-wave and S-wave inverse quality factors, with the ratio of P-wave and S-wave velocities distinguishes gas sand from water sand, and water sand from oil sand. As derived from the analyses, gas sand is characterized by the highest and the lowest ratios; oil sand is characterized by the lowest and the highest ; and water sand is characterized by the and values that plotted between those of the gas and oil sands. The signatures of the bulk modulus, Lame’s first parameter, and compressional modulus show sensitivity to rock fluids. Attenuation analysis in recorded well logs can provide useful guide for hydrocarbon reservoir characterization. (Keywords: Inverse Quality Factor, P-, S- wave, elastic

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Keywords

P-wave elastic modulus, Shear wave elastic modulus, inverse quality factor, amplitude dimunition

Citation

Raji, W. O. and T. O. Adeoye (2014): Petrophysical Sensitivity of Elastic Modulus and Inverse Quality Factor (1/Q) Analysis in Well Logs, Pacific Journal of Science and Technology, Vol. 15(1) 404-414.

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