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.

A newly developed starch based biopolymer treatment to modify the relative permeability curves is presented. The hydrophilic nature of the adsorbed biopolymer causes a reduction in the water relative permeability while having a variable effect on the relative permeability to the non-wetting phase.Starch based biopolymers have excellent viscosity in brines. Their viscosity has been found to increase with an increase in the salt concentration in the brine irrespective of the polymer concentration up to 10,000 ppm. Moreo'Jer, starch is naturally abundant, costeffective, and environmentally safe.

This paper presents an analysis of the temperature and dynamic pressure behavior occuring in a Riserless Drilling (RD) configuration, deepwater well when circulating a ynthetic-based mud (SBM). Also discussed are some aspects of kick detection in this new configuration related to the gas solubility of SBM's. A numerical model has been developed to simulate the mud flow through the Open-Seawater-Drillstring-and-Return-Line configuration system. The simulator is based on the numerical solution for the system of flow equations using finite-difference approximations. The model accounts for the pressure and temperature dependence of mud viscosity and mud density. Through a sensitivity analysis, the effects of pertinent parameters - specially the circulation rate - on the pressures generated in the system are examined. Also, an EOS model was calibrated with PVT data to investigate the swelling of the synthetic-based mud containing dissolved gas. An equation for the solubility of methane in synthetic oil and a procedure for calculating the pit-gain with increasing time are presented. Introduction The petroleum industry is contemplating drilling in waterdepths of 10,000 ft in Brazil and West Africa and possibly 13,000 ft at the turn of the century in the U.S. Gulf of Mexico1. The current offshore technology for deepwater drilling operations requiring the use of a 21-in marine riser seems to have reached its limit at water depths about 7,500 ft. Riserless Drilling appears to be the solution for the challenge that faces the industry today. The RD concept involves utilizing a bare drillstring and a separated nonconcentric return line. A rotating Blowout Preventer (RBOP) caps the return drilling fluid and forces it to circulate through the return line to the surface. A subsea pump is designed to maintain a constant inlet pressure equivalent to the hydrostatic pressure of seawater at the sea floor (Fig. 1). Use of SBM has increased over the last decade in offshore drilling operations because of their lower environmental impact. However, there is a particular problem experienced when designing hydraulic programs with SBM's, i.e., the strong pressure and temperature dependence of SBM density and viscosity. In a RD system the problem tends to be worse following the combination of high pressures with low temperatures at the sea floor. Lost circulation can follow unreliable predictions for equivalent-circulating-density (ECD) made without accounting for the effects of pressure and temperature on SBM density and viscosity. Also, gas is highly soluble in the oil phase of this type of mud. Therefore, the dissolution of gas after a gas kick is taken in a SBM may mask the surface responses and the kick shall travel undetected up to near the surface. Dangerous amounts of gas may be released over a short period of time catching the drilling crew virtually by surprise. For this reason the primary objective of this study is to present a mathematical model to calculate the dynamic pressures during routine drilling operations in a RD system based on the circulating temperature distribution and changes in downhole mud properties with pressure and temperature. The secondary objective is to describe the surface responses associated with a gas kick taken when using SBM in a RD configuration.

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