Suitable sedimentary environment,ecological conditions,favorable spatiotemporal sediment matching and abundant organism—substrate interaction,the Ordovician multiple burrows in the Yingshan Formation and the Yijianfang Formation in the Tahe oilfield,Tarim Basin,overprinted to form a large-scale bioturbated carbonate rock with lateral continuity and vertical connectivity.These bioturbated carbonate rocks have positive porosity and permeability and are potential oil and gas reservoirs. However,it is difficult to identify bioturbated reservoirs using conventional logging data due to the characteristics of strong reservoir inhomogeneity, heterogeneous hydrocarbon-bearing properties,and small differences in logging responses between hydrocarbon-bearing and water-bearing formations.In this paper,the identification model and porosity prediction model for bioturbated carbonate reservoirs in the study area are established by calibrating the well logging data with core data,selecting the most relevant conventional logging parameters.Methods: Based on defining the bioturbation index of the bioturbated Ordovician carbonate cores from 16 wells,calibrating the well logging data with core data,the conventional logging data, such as self-potential,natural gamma,caliper logs,deep laterolog, shallow laterolog,neutron logs and density logs,are selected as the input parameters,and bioturbation index is used as the output results.The rprop,sigmoid symmetri and sigmoid stepwise functions are selected as the training function,the activation function of the hidden layer and the output layer,respectively.The identification model with 3 nodes and 3 layers,is established to identify the Ordovician bioturbated carbonate strata in the study area.The conventional logging data,such as self- potential,natural gamma,caliper logs,sonic logs,Neutron logs and density logs, are selected as the input parameters, and the porosity values from the measured plugs and the Porosity Calculation Sample Inspection Model is used as the output results.The incremental,Gaussian and sigmoid are selected as the training function,the activation function of hidden layer and output layer,respectively.The porosity prediction model with 4 nodes and 3 layers,is established to predict the bioturbated carbonate reservoir in the study area.Results: The identification model established with 3 nodes and 3 layers,is applied to identify the Ordovician bioturbated carbonate strata in the study area and has acquired a positive identification effect.The porosity prediction model established with 4 nodes and 3 layers,is applied to predict the bioturbated carbonate reservoir in the study area and has also acquired a positive prediction effect.Conclusions:The identification model established for bioturbated carbonate reservoirs meet the requirement of accuracy,and are applicable to identify the bioturbated Ordovician carbonate reservoirs in the study area.The prediction model for the porosity of bioturbated carbonate reservoirs meet the requirement of accuracy,which is applicable to the prediction of porosity of the Ordovician bioturbated reservoirs in the Tahe oilfield,Tarim Basin.This study has important reference significance for quantitative characterization of reservoir characteristics,reserve estimation, reservoir description and establishment of reservoir geological model.