The Identity of Petrophysical Properties of Oceanic Serpentinites and Continental Granitoids: Implications for the Recognition of Buried Hydrocarbon-bearing Serpentinite Geobodies

Аннотация

The Earth’s lithosphere is commonly investigated by both direct and indirect methods, corresponding to rock sampling and geophysical surveys, respectively. The interpretation of geophysical data is generally based on the combination of values measured in the lithosphere with those obtained in laboratories from rock samples. However, petrophysical properties of numerous lithotypes overlap, yielding the misleading interpretation of geophysical surveys in many areas of the world. A heated debate particularly concerns non-volcanic rifted margins, fuelled by the possible presence of giant oil and gas fields: thinned continental crust or serpentinized oceanic basement. One of the possible causes of ambiguity is related to the intimate similarity of oceanic serpentinites and various crustal rocks (e.g. basalts, gabbros, limestones, sandstones, shales, etc.), in terms of petrophysical properties. Can variably serpentinized peridotites mimic typical continental crustal rocks, such as granites and granodiorites? To answer this question, we compared literature data of worldwide samples of such lithologies. The results show the complete overlap of the considered petrophysical properties (density, magnetic susceptibility, V_P, V_S, V_P/V_S, and Poisson’s ratio) of these lithotypes (P = 10–1000 MPa, depth = 0.33–33.33 km), further confirming the difficulty in discriminating variably serpentinized mantle rocks from crustal lithologies. Therefore, the recognition of buried serpentinite geobodies, being potential sites of exploitable gas and oil reservoirs, like those probably ensconced in non-volcanic rifted margins, necessitates a robust lithological model inferred from direct methods, namely the study of core drillings, deep-seated xenoliths and tectonic exposures of deep-crustal sections to substantiate the interpretation of geophysical data.