Informational Advantages and Accuracy Characteristics of the Adaptive Well Log Data Interpretation

Abstract

Abstract The adaptive technology of log data interpretation provides heterogeneous reservoirs evaluation in case of framework and clayey cement polymineral composition, notably clastic reservoir rocks. Values of apparent and total porosity are informativeless for such reservoirs. Petrophysical invariant (normalized effective or dynamic porosity) is applied as an interpretative parameter. It characterizes static reservoir properties as well as filtration properties. Proposed petrophysical models use minimum number of physically measureable variables (from core data or from prior petrophysical information about simulated object in core data shortage conditions), which tune interpretation algorithms with high accuracy description of reservoir rocks properties diversity. Effective porosity is estimated using adaptive interpretation of logging data. This procedure is conducted according to characteristic responses derived from each standard log (spontaneous potential, sonic, natural radioactivity, density and neutron logs). Then heterogeneous reservoir properties transfer to geological model. Adaptive technology advantages include following: the technology could be applied for rapid interpretation of log data large volumes; effective porosity could be calculated for complex polymineral reservoirs in absolute units without "reference beds"; the technology provides adaptive tuning on lithological and petrochemical conditions of the particular reservoir in situ, including the wellbore construction influence; it could be used for the old data re-interpretation. Thus, the adaptive log data interpretation practical importance is due to the radical reduction of the error sources number inherent to the conventional technology. The effective porosity prediction from standard log data is an important link in the chain of modern exploration and production activities. Its implementation determines how accurate and detailed a geological model will be and it definitely affects both reserves estimation and the design of a field development plan.