Market prediction of self-sold products in oilfield based on optimized GM (1, 1) model

It is a key link in the expansion of natural gas business to sell independent products in oil and gas high and medium-sized oilfields to transform the advantages of oilfield resources into benefits How to effectively predict the demand of oil and gas products market is very important to improve the oilfield management mechanism and marketing ability In view of the fuzzy market of self-sold products at present, grey prediction can be used from the perspective of data refinement Because the classical GM (1, 1) model is not enough in forecasting accuracy, this paper optimizes the background value and initial conditions that affect the forecasting effect of the model to improve the accuracy of GM (1, 1) model, and establishes a forecasting model for market demand of self-sold products Based on the statistical data of oilfield market demand in recent years, the market demand in the future from 2023 to 2026 is predicted The forecast results show that the market demand is on the rise, and the market demand of self-sold products will have a strong growth state in the future The model achieves the expected goal on the actual market demand data, and has the advantages of simple modeling and strong self-adaptability in application, which provides certain reference value for oilfield to implement independent product sales plan.

Keywords: market demand, Sell products independently, GM (1, 1) model, Background value, Initial condition.