No abstract

Multiple transverse fractures are hydraulically created to enhance the productivity of horizontal wells drilled along with the minimum principal stress. The fracture properties, such as fracture number, length, conductivity, etc, are very important factors affecting the horizontal well productivity. Therefore, a reliable and practicable method for predicting and optimizing the productivity of horizontal wells is essential to reservoir engineering designation. However, existing mathematical models and evaluation methods did not include the impact of the threshold pressure gradient and the pressure-sensitive effect which cannot be ignored in ultra-low permeability reservoirs. The objective of this paper is to present a method considering the threshold pressure gradient and the pressure-sensitive effect, thus predicting and optimizing the productivity of multiple transverse fractured horizontal wells (MFHW) in ultra-low permeability reservoirs becomes available. The new method couples the non-Darcy elliptical flow, which considers the threshold pressure gradient and the pressure-sensitive effect in the reservoir region, the Darcy linear flow in the fractured region, and the Darcy radial flow to the horizontal wellbore in the fractured region respectively. Based on the equality radius mode and the pressure superposition theory, the evaluation methods for the productivity of multiple transverse fractured horizontal wells are presented. In addition, the new method is validated by comparing with field data, results confirm that those formulas are precise and practical, and the evaluation method is reliable. Based on an example of productivity analysis for a multi-fractured horizontal well, the effects of some factors, such as threshold pressure gradient, coefficient of deformation and fracture parameters (fracture number, fracture length, conductivity, uniformity of fractures length and intervals), on the productivity were studied. The results show that the greater the threshold pressure gradient, the greater the effect of it on multi-fractured horizontal well productivity, so the threshold pressure gradient must be accounted to evaluate the MFHW productivity in ultra-low permeability reservoirs. Also, the greater the coefficient of deformation, the greater the effect of it on MFHW productivity, and the affection of coefficient of deformation on productivity is related to producing pressure drop, and the greater the pressure drop, the larger the influence of deformation coefficient on producing rate, thus for strongly pressure-dependent reservoir, we'd better conduct an optimization design for feasible producing pressure drop. In the given condition, the optimal fracture number of the horizontal well is 4~5, the half length of fracture is about 120 m, and the conductivity is 4.8 D•cm. The fractures with longer length, lower conductivity, variable length and placed in unequal interval are favorable for homogeneous oil reservoir. This paper provides reservoir engineers with a reliable and practical method to predict and optimize the productivity of multiple transverse fractured horizontal wells in ultra-low permeability reservoirs.

No abstract

No abstract

After the development of the oil field, it is an important task to predict the production and the recoverable reserve opportunely by the production data. At present, the forecasting methods include reservoir numerical simulation, forecasting model, material balance and production decline, and so on. Of these methods, the forecasting model is a useful and effective one for entire forecasting. The famous Generalized Weng model, Weibull model, Rayleigh model, HCZ model, Hubbert model, Lognormal distribution model are major forecasting models. But these models are all single peak development model, they can't get the reliable results for the bi-peak and multi-peak development model.In this paper a generalized single peak forecasting model and its derived models were established. From the generalized single peak forecasting model, we can derive some famous forecasting models, such as Generalized Weng model, Weibull model, Rayleigh model, Arps Exponential Decline model, Modern model , Modern model , and so on. Subsequently, a multiple peak forecasting model was proposed based on the generalized single peak forecasting model, by which the multipeak model production, cumulative production and recoverable reserve can be obtained. Furthermore, the resolution method of multi-peak forecasting model parameters was also introduced by nonlinear automatic matching solving techniques.According to the practical application for some oil fields, both generalized single peak forecasting model and multiple peak forecasting model are all confirmed to be practical and effective. IntroductionIt is important to forecast the production and recoverable reserve during oil field development and management, and the forecasting model is one of the important methods to predict the future production.Forecasting models can be divided into Periodic model and Growth model according to their characteristics. The Periodic model includes generalized Weng model, Weibull model, Rayleigh model, Gamma model, generalized model, and so on. The Growth model includes HCZ model, Hubbert model (which is also called Logistic model)、logarithmic normal distribution model, normal distribution model, Hu-Chen model and other models 1-12 . The above mentioned models are all based on the single peak development model.On the other hand, bi-peak and multi-peak development models are more constantly displayed during the development of oil field because of putting into production of new block, large scale development adjustment, implement of tertiary oil recovery, and so on. When the oil field development models are bi-peak model, tri-peak model or multi-peak model, it is hard to get the reliable forecasted result only based on single peak model.Based on generalized single peak forecasting model, this paper established the multi-peak forecasting model and its nonlinear multi-parameter automatic matching method. In addition, real data from three oil fields have been adopted to forecast the production, and the results are satisfactory. So the multi-peak forecasting model was ...