Search

The initial productivity of directional oil wells is essential to research during the early development stage of offshore oilfields. Since the influence factors of productivity are numerous, the nonlinear relationship among them and productivity is hard to accurately describe by the physical models in practical application. The data-driven model provides an alternative way to deal with this problem, although it neglects the physical correlation between productivity and its influence factors. Therefore, for combining the advantage of the physical model and data-driven model, the reservoir engineering theory was used to constrain the data-driven method in this study. Based on the eXtreme gradient boosting (XGBoost) trees algorithm, this paper proposed a novel physical constrained data-driven model to predict the initial productivity. The reservoir engineering theory, including the productivity formula and the monotonic correlation between productivity and the input feature, was employed as the physical constraints in this model. Moreover, the Spearman Correlation Coefficient and a modified Recursive Feature Elimination were combined to develop a feature selection method for quantitatively selecting the main influence factors of the initial productivity. Based on the production and geological data from 87 wells, the permeability, completed thickness, oil viscosity, clay content, correct factor for interference, choke size, and drawdown were selected from 19 features as the main influence factors of the initial productivity. The prediction accuracy of the model proposed in this paper is 80.18%, which is better than the previous data-driven models. Furthermore, the physical constraints have been proved to improve the forecasting accuracy of the data-driven method by 10.09%. • A novel physical constrained XGBoost model to predict the initial productivity is developed. • Productivity formula and monotonicity relationship among features are used as physical constraints in the data-driven model. • The reservoir engineering theory is considered to modify the RFE method in the feature-selection process. • The accuracy-enhancing effect of physical constraints on the data-driven algorithm is quantitatively evaluated. [ABSTRACT FROM AUTHOR]

In tilted fault block reservoirs with edge water, the remaining oil is usually formed and located at the structurally highest. The gas and water bidirectional displacement process is an effective method to recover this type of remaining oil in these reservoirs. However, there is no optimizing method to design the injection-production schedule of this process for the maximum oil recovery. In this study, the imaging and superposition principle, Pollock method, equivalence principle, and Buckley-Leverett method were combined to develop a novel semi-analytical method for optimizing the injection-production schedule. An example study was carried out for verifying the proposed semi-analytical method and validated with the numerical simulation method. Furthermore, sensitive factors of this displacement process were quantitatively analyzed by the proposed method. The results showed that the optimized synergy of the gas and water can maximize the oil recovery for the bidirectional displacement process. Compared with no injection, inadequate injection, and excess injection of gas, the breakthrough recovery can be increased by 3.7%, 0.8%, and 4.88%, respectively, by controlling the gas-water synergy. Meanwhile, under the gas-water synergy displacement condition, the oil recovery is increasing with the tilt angle of the reservoir increasing and the distance of well from edge water decreasing. This enhanced oil recovery process is more sensitive to low-middle tilt angles and more effective for small distances. The results obtained from this study can be used to improve the exploitation strategies of tilted fault block reservoir with edge water. • A novel semi-analytical approach is developed to optimize the gas and water bidirectional displacement process. • The dominance for synergy of gas and water bidirectional displacement is verified. • Sensitive factors of gas and water bidirectional displacement are quantitatively analyzed. [ABSTRACT FROM AUTHOR]

The adsorbed methane in shale determines the geological reserves of shale gas and production of the well. Therefore, it is of great importance to clarify the microscopic mechanism of methane adsorption in shale for evaluating the geological condition and formulating exploitation plan. In this study, the experimental data and the simulation result were combined to research the microscopic mechanism of methane adsorption in shale. The experimental data for 99 groups of low-temperature nitrogen adsorption and methane isothermal adsorption were collected, to calculate the number of adsorption layers of methane in shale at the micro-level. The surface, microfracture and micropore structures of the organic matter in shale were constructed by graphite structure with the hydroxyl group. Thereafter, they were used to simulate the interaction potential of the organic matter on methane molecules and the adsorption layer's number by using the theory of intermolecular interaction potential field. Furthermore, the effects of different fracture widths and pore diameters on methane adsorption were analyzed and verified. The results show that the adsorption capacity of methane in shale is related to shale's structure, and the order of the adsorption capacity is surface < microfracture < micropore. Meanwhile, the multilayer adsorption can occur in microfractures with a width of 1.44–1.59 nm and micropores with a diameter of 1.49–1.83 nm, whereas the surface structure just can be the monolayer adsorption. These quantitatively results establish a foundation for the development of adsorption theory for methane in the shale. • The number of adsorption layers is calculated by using experimental data. • The adsorption capacity is ranked as surface < microfracture < micropore. • The number of adsorption layers is quantitatively simulated and analyzed. [ABSTRACT FROM AUTHOR]

Low-velocity non-Darcy flow often occurs in low permeability reservoirs. In this paper, we discuss how to incorporate a non-Darcy flow correction into embedded discrete fracture modeling (EDFM). The resulting method is validated by reproducing type curves containing the characteristic no-flow segment, followed by a nonlinear and a linear segment. Simulation results are also validated against a direct simulation method that uses local grid refinement to (almost) resolve hydraulic fractures. Second, we discuss how grid-based flow diagnostics can be formulated on top of the new EDFM method and used to provide computationally inexpensive predictions of flow patterns, interwell connections, and measures of dynamic heterogeneity. We then demonstrate how such flow diagnostics can be used to optimize well placement and improve oil recovery. • Incorporates a model for low-velocity, non-Darcy flow into embedded discrete fracture modeling (EDFM). • Validates the model against know type curves and direct modeling using local grid refinement to resolve fractures. • Highlights how to use flow diagnostics on top of the non-Darcy EDFM model to provide inexpensive estimates of flow patterns, interwell connections, and measures of dynamic heterogeneity. • Demonstrates how Lorenz coefficient can be used as an inexpensive proxy to optimize well placement. [ABSTRACT FROM AUTHOR]

Solvent-assisted steam flooding has gained popularity in heavy oil reservoir during recent years. Calculating asphaltene deposition is a key issue in developing heavy oil reservoirs, because asphaltene deposition can significantly reduce permeability by blocking pore throats. In this work, a comprehensive model of solvent assisted steam flooding for thin heavy oil reservoirs considering the influence of asphaltene deposition was proposed. The model is solved by IMPES (Implicit Pressure and Explicit Saturations) method. The amount of deposition is calculated through three mechanisms of entrainment, plugging deposition and surface deposition. Then, the effects of asphaltene deposition on well performance and permeability reduction were analyzed. Furthermore, the solubility parameter is used to investigate the effect of different solvents on alleviating the damage of asphaltene deposition for reservoir. The damage of asphaltene deposition for reservoir can decrease with the increase of solvent concentration. Finally, based on the analysis of oil production, it is found that butane assisted steam flooding is the most effective thermal method to improve the oil recovery. And injection parameters of butane assisted steam are also determined for an oil field by analysis of oil production. Based on the results in this paper, it may be extensive applicability and practical significance for determining the best solvent and reasonable injection parameters during the development of heavy oil reservoirs considering asphaltene deposition to enhance oil recovery. • A mathematical model has been developed to evaluate the performance of solvent assisted steam flooding considering asphaltene deposition. • The effects of asphaltene deposition on well performance and permeability reduction were analyzed. • The solubility parameter is used to investigate the effect of different solvents on alleviating the damage of asphaltene deposition. • The production performance by adding different solvents is compared. [ABSTRACT FROM AUTHOR]