Predicting porosity in tight sandstone reservoirs based on logging while drilling engineering parameters

Reservoir porosity is a crucial indicator of the physical properties of reservoirs, forming the foundation for oil and gas exploration, development design, and decision-making. Currently, it is primarily obtained through core testing or logging interpretation, but the lack of quantitative evaluation methods during drilling limits the timeliness and efficiency of porosity acquisition. Based on this, this study focuses on the tight sandstone reservoir in the East China Sea shelf basin, conducting modeling and rock-breaking simulations of 5 blade and 6 blade polycrystalline diamond compact (PDC) bits commonly used in the region. It investigates the relationships between rate of penetration (ROP), torque, mechanical specific energy (MSE), physical index, and other parameters for rocks with varying physical characteristics. A real-time quantitative prediction method for reservoir porosity, based on drilling and logging engineering parameters, is proposed. The results indicate that: (1) Significant differences in the response characteristics of rate of penetration, torque, and MSE are observed when drilling formations with identical mechanical characteristics, due to the influence of bit type. Therefore, these engineering parameters are not suitable for directly predicting reservoir porosity. (2) The relationship between the physical index and elastic modulus for 5 blade and 6 blade PDC bits is highly consistent, with both increasing logarithmically as elastic modulus increases. This suggests that the physical index can eliminate the influence of bit type and more accurately reflect changes in formation characteristics during drilling. (3) Using elastic modulus as an intermediary parameter, a model is established that relates porosity to the physical index, showing that porosity decreases as a power function of the physical index. The research findings were cross-verified in well NB13-4-A, with a 91.57% agreement between the porosity predicted by engineering parameters and the logging-derived porosity. The prediction method was applied to 20 exploration wells in the NB13-4 working area, yielding an average porosity consistency rate of 85.74%. This demonstrates that the method can provide timely, efficient, and accurate support for decision-making in exploration operations, such as intermediate testing and well completion.