Shale gas, with its lower carbon content and pollution potential, is the most promising natural gas resource in China. When modeling the shale gas supply in a specific gas field, it is of paramount importance to determine the gas supply under economic considerations. Two common calculation methods are used in China for this purpose: Method 1 (M1) is the breakeven analysis, where the gas supply ...

The knowledge and the forecast of the parameters which rule the down flow models in oil extraction and transport are today of paramount importance. In particular the extracted oil is mixed with water and gas in rates, which differ not only from different wells, but also on the same well during its life. The main problems involved with the measurement of the flow rates are: well exhaustion, crit...

Gold price forecast is of great importance. Many models were presented by researchers to forecast gold price. It seems that although different models could forecast gold price under different conditions, the new factors affecting gold price forecast have a significant importance and effect on the increase of forecast accuracy. In this paper, different factors were studied in comparison to the p...

The hyperbaric oxygen inhaled at the pressure od 2-3 atmospheres raises considerably the blood concentration of the gas, which becomes sufficient for tissular needs sometimes without soliciting hemoglobin intervention. This makes possible the survival of some tissues insufficiently supplied with blood. We forecast therapeutical indications in diabetic retinopathy, hypertensive retinopathy, reti...

Nowadays, there exist various methods for modelling and forecasting foreign exchange (FX) rates including economical models, statistical methods and learning neural networks. Dealing with the problems of nonstationarity and nonlinearity has been a challenge. In this paper, we propose a combined neural model for effectively tackling the problems. The model is termed as neural gas mixture of auto...

We are concerned with robust and accurate forecasting of multiphase flow rates in wells and pipelines during oil and gas production. In practice, the possibility to physically measure the rates is often limited; besides, it is desirable to estimate future values of multiphase rates based on the previous behavior of the system. In this work, we demonstrate that a Long Short-Term Memory (LSTM) re...

In the oil and gas industry, energy prediction can help the distributor and customer to forecast the outgoing and incoming gas through the pipeline. It will also help to eliminate any uncertainties in gas metering for billing purposes. The objective of this paper is to develop Neural Network Model for energy consumption and analyze the performance model. This paper provides a comprehensive revi...

In this article, we forecast crude oil and natural gas spot prices at a daily frequency based on two classification techniques: artificial neural networks (ANN) and support vector machines (SVM). As a benchmark, we utilize an autoregressive integrated moving average (ARIMA) specification. We evaluate outof-sample forecast based on encompassing tests and mean-squared prediction error (MSPE). We ...

Fossil energy markets have always been known as strategic and important markets. They have a significant impact on the macro economy and financial markets of the world. The nature of these markets are accompanied by sudden shocks and volatility in the prices. Therefore, they must be controlled and forecasted by using appropriate tools. This paper adopts the Generalized Auto Regressive Condition...