Quantification of Hydrocarbon Volume: An Example Using Rock Typing Methodology Applied in Cerro Negro Field, Eastern Venezuela Basin

Abstract

For many years, geologists and engineers have used volumetric methods to quantify or estimate hydrocarbon volume contained in reservoirs. The economic producibility of the reservoirs, also depend on the flow characteristics. The overall level of uncertainty of the estimation depends on the uncertainty of the parameters that determine the oil volume such as porosity and the reservoir characteristics such as pay thickness. However, uncertainty of estimation increases when estimating hydrocarbon in place for complex fluids systems (i.e. heavy oil) since mobility can have an adverse effect on fluid movement. Determination of net pay cut-offs should be based on parameters that include flow and storage capacity.Considering the requirement to establish a relationship between petrophysical cut-offs and rock types to estimate hydrocarbon in place, five different cases were used to quantify net pay parameters of the reservoir in the Cerro Negro field, Venezuela. The workflow that was applied: 1. Identification of petrophysical rock types (PRT) from porosity and permeability data using core-based and log-derived petrophysical analysis, 2. Definition of the relationship between PRT and facies 3. Determination of pay cut-offs for reservoir and each PRT using conventional and contemporary methodologies, 4. Comparison of the conventional and contemporary methodologies results, 5. Estimation of pay cut-offs impact on the prediction of rock types and reservoir petrophysical properties in the estimation of volumetric. This study demonstrates that the definition of PRT distribution is controlled by pore throat size instead of facies. From the six rock types defined in the field just three rock types (1, 2, and 3) are oil producing rock reservoir. The OOIP results vary significantly over a range of 500 MMstb, depending on which of the parameters are used as pay cut-offs. In conclusion, estimating OOIP by applying petrophysical rock typing is an improved way to decrease uncertainty than OOIP estimation by reservoir unit. The results demonstrated that the choice of good pay cut-offs was the key to reduce the uncertainty in the estimation of the OOIP in the Cerro Negro field.