油气产量预测的GM(1,1)幂模型

GM(1,1) Power Model for Prediction of Oil and Gas Production

摘要: Arps递减模型是目前应用最广的油气产量预测模型，但对测试序列要求高。GM(1,1)幂模型能适应多种形状序列的建模预测。根据二者形式上的相似性，将GM(1,1)幂模型看成Arps模型的扩展。利用GM(1,1)幂模型推导了产量及产量递减率预测公式，建立以误差最小为目标的优化模型求解参数，并利用粒子群算法求解。通过实例证明：利用GM(1,1)幂模型进行产量预测，建模精度更高，适用范围更广。

Abstract: Arps decline model was the most widely used model for predicting oil and gas production at present, but it had a high requirement for test sequences. The GM(1,1) power model was appro-priate for the modeling forecast of multiform sequence. Based on the similarity between the Arps decline model and GM(1,1) power model, this paper regards the GM(1,1) power model as the extension of the Arps decline model. The GM(1,1) power model was taken as the expansion of Arps model; the GM(1,1) power model was used to deduce the predicting formulae of production and production decline rate, and build the optimization model with the objective function that the error was minimal and the particle swarm optimization algorithm was used to solve the problem. It is proved by examples that the modeling accuracy is higher and the range of application is wider by using GM(1,1) power model to predict output.