Rock Physics Diagnostics as a prerequisite for optimal Petrophysics
Year: 2021
basins:
Proceedings Title : PROCEEDINGS, INDONESIAN PETROLEUM ASSOCIATION, Forty-Fifth Annual Convention & Exhibition, 1 - 3 September 2021
One of the key outputs from petrophysical evaluation is porosity. Sonic log is considered as one of the logs for deriving petrophysical volumes including porosity. However, the sonic data might not be always suitable to be included in the petrophysical model even if the quality of the log is quite good. One of the key reasons lies behind the variable porosity-velocity relationship for different types of formations attributed to post depositional processes. Without performing proper rock physics diagnostics before petrophysics model building can create inconsistencies in the petrophysical volumes as well as force the petrophysicist to use unreasonable endpoints for matrix or fluid. In this paper, an attempt is made to perform rock physics diagnostics using Wyllie-time-average and Raymer-Hunt-Gardner relations, drawing conclusion on the consolidation state of the rock, followed by computation of porosity from sonic using these relations. Later, rock physics diagnostic using theoretical rock physics models is carried out to confirm and complement this understanding of rock’s consolidation state. The results show that even though these empirical relations in their original form are useful and widely used but it is not quite suitable for unconsolidated and weakly cemented (poorly consolidated) formations or at least cannot justify the porosity-velocity trend in the data. Here computed sonic porosity is compared with field calibrated density porosity. It could be seen from this study that, in order to match sonic porosity with density porosity, an unreasonable matrix/fluid endpoints or non-theoretical empirical fitting coefficient is required. Since, this might not always be the case, a proper assessment using rock physics diagnostic should be carried out before incorporating sonic data into the petrophysical model.
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