Comprehensive workflow to quantify diagenetic cement from wireline logs of deep water east coast of India wells and rock physics modeling

Abstract

Presence of diagenetic cement is common in deep-water siliciclastic reservoirs and largely affects reservoir quality. Hence, the quantification of cement volume is an integral part of the reservoir characterization workflow. Lab analysis of core samples provides the cement volume information used as input for rock physics modeling. In the absence of core sample analysis, use of analogous offset well information provides an approximate estimate of cement. In reality, most deep-water wells do not have core samples for lab analysis. Consequently, the availability of offset well information is sparse and sometimes unavailable. Hence, getting an accurate cement volume estimate for reservoir characterization is challenging. For a detailed analysis, it is desirable to have a continuous measurement of cement volume across the reservoir sand. Presence of a calibrated cement volume log for the entire reservoir improves rock physics modeling. In this work, petrophysical M-N lithology cross plot, which is widely used to identify lithologies, has been used to quantify the diagenetic cement present within the reservoir, where M is the density normalized sonic values and N is the density normalized neutron values. Here, the M and N has been used as M-Lithology (MLITH) and N-Lithology (NLITH). In estimating MLITH and NLITH values, compressional sonic, bulk density and neutron logs are used. Porosity estimated from neutron/density is useful to identify the type of cement. Whereas, sonic slowness values are more sensitive towards the amount of grain contact cements. Hence, the estimated values of MLITH and NLITH varies differently in the presence of diagenetic materials. These variations of MLITH and NLITH values are captured and converted to cement volume fractions. In the presence of core data, the lab analysis measurements are used to calibrate the cement volume log. Further, rock physics modeling results helps to validate the output. The results of the study add value by quantifying diagenetic cementation in the reservoir characterization process by mitigating the associated limitations due to absence of sufficient core data.