In the early time of oilfield development, insufficient production data and unclear understanding of oil production presented a challenge to reservoir engineers in devising effective development plans. To address this challenge, this study proposes a method using data mining technology to search for similar oil fields and predict well productivity. A query system of 135 analogy parameters is established based on geological and reservoir engineering research, and the weight values of these parameters are calculated using a data algorithm to establish an analogy system. The fuzzy matter-element algorithm is then used to calculate the similarity between oil fields, with fields having similarity greater than 70% identified as similar oil fields. Using similar oil fields as sample data, 8 important factors affecting well productivity are identified using the Pearson coefficient and mean decrease impurity (MDI) method. To establish productivity prediction models, linear regression (LR), random forest regression (RF), support vector regression (SVR), backpropagation (BP), extreme gradient boosting (XGBoost), and light gradient boosting machine (LightGBM) algorithms are used. Their performance is evaluated using the coefficient of determination (R²), explained variance score (EV), mean squared error (MSE), and mean absolute error (MAE) metrics. The LightGBM model is selected to predict the productivity of 30 wells in the PL field with an average error of only 6.31%, which significantly improves the accuracy of the productivity prediction and meets the application requirements in the field. Finally, a software platform integrating data query, oil field analogy, productivity prediction, and knowledge base is established to identify patterns in massive reservoir development data and provide valuable technical references for new reservoir development.

Naturally fractured gas reservoirs have contributed significantly to global gas reserves and production. The classical gas-well decline analysis relies largely on Arps’ empirical decline models, or modern production decline analysis associating with pseudo-variables. The explicit original gas in place determination methodology is extended from homogeneous reservoir to naturally fractured reservoir under constant or variable bottom-hole pressure conditions in gas-well rate decline analysis. Then, the relationship between gas flow rate and average reservoir pseudo-pressure in the boundary-dominated flow period is re-derived. This formula is in the same format with the equation for homogeneous reservoir by due to the introduction of a new productivity index parameter that captures the inter-porosity flow between fracture and matrix in the natural fractured reservoir. The proposed step-by-step procedures are applied here, which enable the estimation of decline exponent and the explicit and straightforward determination of the original gas in place without any iterative calculations. Four simulated cases prove that our methodology can be successfully used in heterogeneous naturally fractured reservoirs with irregular boundary under constant or variable bottom-hole pressure conditions.

A numerical pressure transient analysis method of composite model with alternate polymer flooding is presented, which is demonstrated by field test data provided by China National Petroleum Corporation. Polymer concentration distribution and viscosity distribution are obtained on the basis of polymer rheological model, considering shear effect, convection, diffusion, inaccessible pore volume and permeability reduction of polymer. Pressure analysis mathematical model is established by considering wellbore storage effect and skin effect. Type curves are then developed from mathematical model which have seven sections and parameter sensitivity is analyzed, among which the transient sections of low-concentration and high-concentration hydrolyzed polyacrylamides (HPAM) solution, high-concentration HPAM solution and crude oil show obvious concave shape on pressure derivative curve due to different viscosities of three zones. Formation parameters and viscosity distribution of polymer solution can be calculated by type-curve matching. The polymer flooding field tests prove that the three-zone composite model can reasonably calculate formation parameters in onshore oilfield with alternate polymer flooding, which demonstrate the application potential of the analysis method.