Abstract: The genetic method with basin modeling as the core has been widely used in hydrocarbon exploration and production. China’s basin modeling theory and research are in the front ranks of countries of the world, but the application software development lags far behind other countries. According to statistics, 75 % of the 39 pieces of basin modeling software or algorithms available in China are developed by foreign companies, and 100 % of the popular software on the international market are developed by overseas companies. At present, the main challenge faced by basin modeling research is that the classical petroleum system theory widely applied in the past cannot effectively evaluate unconventional oil-gas resources. In this study, whole petroleum system theory is adopted to address the current challenges. Firstly, the basic characteristics, genetic mechanism and distribution regularities for the joint coexistence of conventional and unconventional oil-gas resources are elaborated based on the whole petroleum system theory, providing theoretical and methodological guidance for the prediction and assessment of conventional and unconventional oil-gas resources. Secondly, key technologies for predicting and assessing conventional, tight and shale oil-gas resources have been developed by establishing a combined genetic model for conventional and unconventional oil-gas reservoirs and a material balance relationship between total hydrocarbon generation and hydrocarbon resources. Thirdly, this paper establishes five sets of material balance equations between the total hydrocarbon production and the evolution and productivity of the whole petroleum system, analyzes the key geological parameters such as primitive hydrocarbon production ratio, migration-accumulation coefficient, movable hydrocarbon ratio and oil recovery, and proposes 12 key technologies of three categories for basin modeling. The new generation basin modeling system based on the whole petroleum system theory and modern information technology is expected to achieve quantitative, automated and intelligent assessment of oil-gas resources, increase the total amount of resources as the study objects by 5 to 8 times, deepen the research of predicted and assessed resources by more than 3 times, significantly improve the reliability of the predicted and assessed results, and solve the existing bottleneck problem.