Geostatistical Model Construction for Oil Reservoirs: Equivalence of Vector Property Components to their Simulation (#236)
Read ArticleDate of Conference
July 17-19, 2024
Published In
"Sustainable Engineering for a Diverse, Equitable, and Inclusive Future at the Service of Education, Research, and Industry for a Society 5.0."
Location of Conference
Costa Rica
Authors
Portilla-Lazo, Carlos
Tumbaco-Cruz, Gabriel
Escobar-Segovia, Kenny
Malavé-Carrera, Carlos
Chipe Del Pezo, Laura
Abstract
Within the geostatistical models that are built are those that characterize the petrophysical properties of the reservoir, however, as is known, the information about the petrophysical nature of the reservoir originates from electrical records that are run in an open hole. in the well after drilling and also by means of cores that are obtained during drilling, the latter have some disadvantages, the data obtained from these are not always reliable because they are small, also, that these cores also show contamination due to drilling fluid. This study sought to analyze whether the vector component of a property is the product of other components that can be analyzed separately, referring to the aforementioned, the following example could be considered, the product for this demonstration can be a petrophysical property such as effective porosity since this property is dependent on its components, which in this case would be the Density porosity models, the Neutron Log porosity and the clay volume model, this conclusion can be reached because these values are the variables that are generally used in the equations that are used when performing the effective porosity evaluation. The result of this investigation gives the professional an additional tool to verify if there is a correct distribution of the petrophysical properties within the reservoir and that it is as realistic as possible. In other words, this study will optimize the alternatives to make the right decision. at the moment that it is required to verify the estimate of the real data with the estimated data.