Porosity analysis of micro-electric imaging logging and its application in carbonate reservoir production capacity forecast

Through a thorough study on measurements of micro-electric imaging logging, a resistivity scaling formula based on the low frequency components is proposed, combined with Archie's equation and introduction of conventional logging data and processing results, an algorithm which can directly convert mico-electric imaging logging data into porosity was strictly derived. With this method, resistivity scaling process and direct application of Archie formula can be avoided, thus the processing is simplified, and impacts of a variety of uncertainties such as a, b, n, S xo and R mf in Archie formula and shallow investigation laterolog R LLS for the results can be eliminated, which maximize a self-adaptive processing of the data. Consequently, a variety of statistical analysis was made upon the porosity spectrum, an interval porosity analysis similar to NMR is carried out, a porosity radial heterogeneity analysis similar to permeability evaluation in reservoir description was also made. Programming with Visual C++, a software has been developed and applied in carbonate reservoir capacity forecast. For the first time we proposed the concept of "porosity contribution factor". By regression analysis of the logging data and the oil testing data of the study area, a fitting formula of oil-producing intensity and porosity contribution factor was established.