World gas supply forecasting has proved difficult because its exploration, transportation, and customer bases are so heavily dependent on fluctuating economic factors. Our recent study showed that the conventional Hubbert model with one complete production cycle is not appropriate for use in forecasting gas production trends for most gas producing countries. This paper presents our forecast for the world's supply of conventional natural gas to the year 2050. We used a multicyclic Hubbert approach to develop 53 country-specific gas supply models that enable production forecasts for virtually all of the world's gas. The multicyclic modeling approach is presented in a convenient form that makes production data exhibiting two or more cycles easier to model. These models were aggregated to the regional level and to the world level. Supply models for some organizations (e.g. OPEC, non-OPEC, OECD) were also developed and analyzed. Our results indicate that the world's supply of natural gas will peak in 2014, followed by an annual depletion rate of 1%/yr. A regional analysis indicates that gas production of some regions will peak soon. North American gas production is currently (1999) at its peak. West European gas production is expected to peak in 2002. The countries of the former Soviet Union and Middle East, which comprise about 60% of world's ultimate recovery of natural gas, will be the main sources of world gas supply in the future. Introduction Natural gas is becoming an increasingly important source of the world's energy. In recent years, natural gas has become the fastest growing fossil fuel, and it will continue to grow rapidly for several decades. The US Energy Information Administration (EIA)1 reported that the world's gas consumption grows by 3.3%/yr compared to 2.2%/yr for oil and 2.1%/yr for coal. This higher growth rate can be attributed to several factors. First, natural gas, including unconventional gas, is available in abundant quantities in many parts of the world. Second, natural gas is environmentally cleaner than coal and crude oil. Third, the lower price of gas relative to other fuels makes it attractive to many gas operators and consumers. Fig. 1 shows the U.S. wellhead prices of gas and crude oil since 1949. These data are wellhead inflation-adjusted prices based on 1992 U.S. dollars on an equivalent energy basis. The figure shows that there is a somewhat direct relationship between oil and gas prices, with a time lag of 3 to 4 years. In 1949, the gas/oil price ratio was 0.12, indicating that gas was 12% as valuable as oil on an energy basis. Since that time the trend of this ratio has been increasing generally upward, reaching the value of 0.94 in 1998. This indicates that gas has now reached a close price parity with oil. The gas industry is influenced by political events, economic factors, and its relationship with the oil industry. Fig. 2 shows the U.S. marketed gas production rate since 1918. The gas production trend from 1918 until 1970 shows an exponential growth. From 1970 to 1973, gas production continued to increase, but at a slower rate of growth. Oil production peaked in 1970. Contributing factors to the slow-down in gas rate increases might have been the oil production decline, which resulted in a decline of associated gas production, and lower gas prices. However, there were gas supply shortages in the very cold winter of 1972–1973. Actual gas production peaked in 1973, the time OPEC cut production of crude oil. Then gas production rates dropped, paralleling the decline in oil production. This drop in gas rate extended to 1975 since the gas market was based on long-term gas sales contracts with stable prices. During the 1975–1979 period, gas production showed slow growth and gas prices became more extensively regulated. In 1979, the Iranian revolution caused oil prices to increase sharply reaching the peak in 1981. This corresponded to an increase of gas prices, which peaked in 1984 (Fig. 1.) The oil/gas price time lag of three to four years possibly resulted from the moderating effect of long-term gas contracts. In 1981, with low gas demand, the " gas bubble" and gas production decreased rapidly until 1986 despite the fact that gas reserves and production capacities were high.

Summary Equilibrium ratios play a fundamental role in the understanding of phase behavior of hydrocarbon mixtures. They are important in predicting compositional changes under varying temperatures and pressures conditions in reservoirs, surface separators, production and transportation facilities. In particular they are critical for reliable and successful compositional reservoir simulation. This paper presents a new approach for predicting K-values using Neural Networks (NN). The method is applied to binary and multicomponent mixtures, K-values prediction accuracy is in the order of the tradition methods. However, computing speed is significantly faster. Introduction Equilibrium rations, more commonly known as K-values, relate the vapor mole fractions (yi), to the liquid mole fraction (xi) of a component (i) in a mixture, (1) In a fluid mixture consisting of different chemical components, K-values are dependent on mixture pressure, temperature, and composition of the mixture. There are a number of methods for predicting K-values, basically these methods compute K-values explicitly or iteratively. The explicit methods correlate K-values with components parameters (i.e. critical properties), mixtures parameters (i.e. convergence pressure). Iterative methods are based on the equation of state (EOS) and are, usually, tuned with binary interaction parameters. Literature search and experience in the phase behavior of hydrocarbon systems, have shown that current explicit methods are not accurate because they neglect compositional affects. EOS approach requires extensive amount of computational time, may have convergence problems, and must be supplied with good binary interaction parameters. In compositional reservoir simulation where million of K-values are required, the method becomes time consuming and adds to the complexity of simulation studies making some of them impractical. Neural Networks (NN) are emerging technology that seems to offer two advantages, fast computation and accuracy. The objective of this paper is to show the potential of using NN for predicting K-values. Different NN where trained using the Scaled Conjugate Gradient (SCG), and where used to predict the K-values for binary and multicomponent mixtures.

TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractThe industrial and residential market for natural gas produced in the United States has become increasingly significant. Within the past ten years the wellhead value of produced natural gas has rivaled and sometimes exceeded the value of crude oil. Forecasting natural gas supply is an economically important and challenging endeavor. This paper presents a new approach to predict natural gas production for the United States using an artificial neural network.We developed a neural network model to forecast U.S. natural gas supply to the Year 2020. Our results indicate that the U.S. will maintain its 1999 production of natural gas to 2001 after which production starts increasing. The network model indicates that natural gas production will increase during the period 2002 to 2012 on average rate of 0.5%/yr. This increase rate will more than double for the period 2013 to 2020.The neural network was developed with an initial large pool of input parameters. The input pool included exploratory, drilling, production, and econometric data. Preprocessing the input data involved normalization and functional transformation. Dimension reduction techniques and sensitivity analysis of input variables were used to reduce redundant and unimportant input parameters, and to simplify the neural network. The remaining input parameters of the reduced neural network included data of gas exploratory wells, oil/gas exploratory wells, oil exploratory wells, gas depletion rate, proved reserves, gas wellhead prices, and growth rate of gross domestic product. The three-layer neural network was successfully trained with yearly data starting from 1950 to 1989 using the quick-propagation learning algorithm. The target output of the neural network is the production rate of natural gas. The agreement between predicted and actual production rates was excellent. A test set, not used to train the network and containing data from 1990 to 1998, was used to verify and validate the network performance for prediction. Analysis of the test results shows that the neural network approach provides an excellent match of actual gas production data. An econometric approach, called stochastic modeling or time series analysis, was used to develop forecasting models for the neural network input parameters. A comparison of forecasts between this study and other forecast is presented.The neural network model has use as a short-term as well as a long-term predictive tool of natural gas supply. The model can also be used to examine quantitatively the effects of the various physical and economic factors on future gas production.

Summary World gas supply forecasting has proved difficult because its exploration, transportation, and customer bases depend so heavily on fluctuating economic factors. Our recent study showed that the conventional Hubbert model with one complete production cycle is not appropriate to use to forecast gas-production trends for most gas-producing countries. This paper presents our forecast for the world's supply of conventional natural gas to Year 2050. We developed a "multicyclic Hubbert" approach that accurately models the gas-production history of each gas-producing country. Models for all countries were then used to forecast future production of natural gas worldwide. We present the multicyclic modeling approach in a convenient form that makes production data that exhibit two or more cycles easier to model and aggregated these models to regional and world levels. We also developed and analyzed supply models for some organizations [e.g., the Organization of Petroleum Exporting Countries (OPEC), the Organization for Economic Cooperation and Development (OECD), the European Union (EU), and the Intl. Energy Agency (IEA)]. Our results indicate that the world supply of natural gas will peak with a plateau production of 99 Tcf/yr from 2014 to 2017, followed by an annual depletion rate of 1%/yr. Regional analyses indicate that gas production of some regions will peak soon and that North American gas production is now (1999) at its peak. West European gas production is predicted to peak in 2002. Former Soviet Union (FSU) and Middle East countries, which contain approximately 60% of the world's ultimate recoverable natural gas, will be the main sources of supply in the future. Introduction Natural gas is becoming an increasingly important source of the world's energy. In recent years, natural gas use has grown the fastest of all the fossil fuels, and it will continue to grow rapidly for several decades. The U.S. Energy Information Admin. (EIA)1 reported that world gas consumption grows by 3.3%/yr compared with 2.2%/yr for oil and 2.1%/yr for coal. This higher growth rate can be attributed to several factors. First, natural gas, including unconventional gas, is available in abundant quantities in many parts of the world. Second, natural gas is environmentally cleaner than coal and crude oil. Third, the lower price of gas relative to other fuels makes it attractive to many gas operators and consumers. Fig. 1 shows the U.S. wellhead prices of gas and crude oil since 1949. These data are wellhead inflation-adjusted prices based on 1992 U.S. dollars on an equivalent-energy basis. The figure shows that a somewhat direct relationship exists between oil and gas prices, with a time lag of 3 to 4 years. In 1949, the gas/oil price ratio was 0.12, indicating that gas was 12% as valuable as oil on an energy basis. Since that time, the trend of this ratio has been generally upward, reaching a value of 0.94 in 1998, indicating that gas has now reached a close price parity with oil. The gas industry is influenced by political events, economic factors, and its relationship with the oil industry. Fig. 2 shows the U.S. marketed-gas production rate since 1918. The gas-production trend from 1918 to 1970 shows exponential growth. From 1970 to 1973, gas production continued to increase but at a slower rate. Oil production peaked in 1970. Contributing factors to the slowdown in gas-rate increases might have been the oil-production decline, which resulted in a decline of associated gas production and lower gas prices. However, gas-supply shortages occurred during the very cold winter of 1972-73. Actual gas production peaked in 1973, when OPEC cut production of crude oil. Then, gas-production rates dropped, paralleling the decline in oil production. This drop in gas rate extended to 1975 because the gas market was based on long-term gas-sales contracts with stable prices. During 1975-79, gas production showed slow growth and gas prices became more extensively regulated. In 1979, the Iranian revolution caused oil prices to increase sharply, reaching a peak in 1981. This corresponded to an increase of gas prices, which peaked in 1984 (Fig. 1). The oil/gas price time lag of 3 to 4 years possibly resulted from the moderating effect of long-term gas contracts. In 1981, with low gas demand, the "gas bubble" (time period of high gas reserves and production capacity and low demand) and gas production decreased rapidly until 1986, despite the fact that gas reserves and production capacities were high. Since 1986, gas production increased steadily for a variety of reasons, including government policy and tax incentives, increased gas demand caused by fuel switching and low gas prices, and increases in unconventional gas production.2 Of considerable interest to both producers and consumers is the future direction of U.S gas production. Our recent study3 indicated that Hubbert's model,4–7 which proved useful for oil-production forecasting, does not account for fluctuations in gas-producing rates. Thus, it may not be appropriate for forecasting gas production for the U.S. and a number of other countries. This paper presents new forecasting models for the future gas supply. Our supply models are based on country-by-country production analyses. We also discuss natural gas supply analysis by region and by organization or group.