Recovery of superheavy oils and tars from thin reservoirs poses formidable technical challenges.The steam injectivity achievable with conventional steamflood processes is low and will generally result in low recovery and poor thermal efficiency. In a second pilot test of the fracture-assisted steamflood technology (FAST) process, Conoco Inc. demonstrated that the process can be used to recover efficiently -2 to 3°API [1.093-to 1.052-g/cm 3 ] tar in south Texas. This paper describes the pilot design and operation. Results of a variety of project monitoring and evaluation techniques, such as temperature surveys, reservoir tracer tests, seismic reflection mapping, and postpilot coring, are reviewed. In addition, the results of a numerical simulation model used for a history match of the pilot performance are described. On the basis of these data, conclusions regarding the dominant flow mechanisms are made.

A grid refinement study of an actual hydrocarbon miscible gas injection improved oil recovery project was made using an equation-of-state compositional reservoir simulator developed at The University of Texas (UTCOMP). A vertical cross- section of this massive carbonate reservoir was simulated using up to 95 permeability layers based upon an extensive characterization program done by Conoco Inc. The primary motivation of this study was to determine the dependence of the predicted oil recovery on the gridblock size. The initial expectation based upon the literature was that if very large gridblock sizes were used in a study planned to be done with a commercial reservoir simulator using conventional one-point upstream weighting and no physical dispersion, then the results would not be very accurate. This is because of numerical dispersion, especially since this was a multiple contact miscible (MCM) process requiring flash calculations in large gridblocks UTCOMP has a third-order-correct finite-difference approximation option and both this option and one-point upstream weighting were used so that comparisons could be made and plans made for what gridblock size to use with the commercial simulator. Contrary to what is in the literature, our results show that the effect of numerical dispersion is very problem dependent and not always large even for an MCM process. For the reservoir studied, our simulations show that the oil recovery is quite insensitive to mesh refinement at both low pressure, below minimum miscibility pressure (MMP), and high pressure. UTCOMP showed very nice linear convergence when the grid was refined. This is not true for all simulators and must be checked, and it is very important. We also found that surprisingly large gridblocks (up to 100 feet in the flow direction) can be used in this case before the errors in oil recovery become large, and that there was not very much difference between third-order and first-order approximations. We think that this is due to the dominance of the layering, and so both an accurate reservoir description and a careful grid refinement must be made on each problem. This has new and very important implications with respect to how field studies of miscible floods should be done and how accurate they will be in predicting the oil recovery. Introduction It is well recognized that physical dispersion is important in miscible gas displacements. Most of the commercial finite-difference compositional simulators currently available for miscible flood predictions and designs use either the one-point or two-point upstream weighting scheme to evaluate the coefficients of the convective terms and thus are subject to large truncation errors resulting in what is commonly known as numerical dispersion. However, the artificial numerical dispersion introduced by the one-point upstream weighting scheme, which in one-dimensional problems is approximately equivalent to a physical dispersivity of x/2, is often larger than the true physical dispersion unless very small gridblocks are used. Consequently, in reservoir-scale problems, gridblock size would have to be intractably small for the numerical dispersion to be on the order of realistic physical dispersion. In addition to grid size, the magnitude of this numerical dispersion is also sensitive to grid orientation. The two-point upstream method produces more accurate results than the one-point upstream method, but the numerical dispersion and grid orientation effects are not eliminated. The effects of numerical dispersion and related issues on miscible gas floods have been an active subject of investigation. This is because inaccuracies arising from numerical dispersion can lead to erroneous solutions and misrepresent the physics of the displacement process. P. 359^

Conventional steamflooding of heavy oils and tars in thin reservoirs generally suffers from excessive heat losses to the over- and under-burden. High rate steam injection is often constrained by limited reservoir injectivity. A recently developed FAST process (Fracture-Assisted Steamflood Technology) allows high rates of steam injection in thin shallow sands through hydraulically created horizontal fractures. This process limits the heat losses by shortening the steamflood life for a 5 to 7.5 acre (2 to 3 ha) pattern to less than two years. Conoco demonstrated the technical feasibility of the FAST process in two pilot tests in south Texas where −2 ° API (1 093 kg/m3) tar was successfully produced. In an attempt to understand the dominant flow mechanisms in the FAST process and to develop a technique for predicting performance of future FAST steamfloods, numerical simulation was used to achieve a comprehensive history match of the second pilot test at the Saner Ranch in south Texas. Despite the complexity of this recovery process, a commercially available steamflood simulator was used to match the performance of one-twelth symmetry element of the inverted 7-spot, 7.5 acres (3 ha) pattern. In addition to matching the tar and water production, the temperature and pressure histories, temperature profiles, water cuts and volumetric tar recoveries were also matched. One of the key elements was the modeling of multiple phase flow through an open fracture. This was accomplished by a simple technique which did not require reprogramming of the conventional steamflood simulator. The numerical simulation of the FAST process revealed dominant flow mechanisms in the process. The calibrated model is now being used for on-going predictive and process optimization studies. This paper briefly describes the FAST process, pilot history, details of the technique used to model flow in an open fracture, and results of the numerical modeling study. Introduction Conoco conducted two pilot tests of the FAST steamflood process in the south Texas tar sands deposits (Fig. 1). These formations contain −2 ° to + 3 ° API (1 093 to 1 052 kg/m3) tar with viscosities of 1 to 20 million centipoise at reservoir temperatures. The first pilot was conducted from November 1977 to June 1980 at the Street Ranch lease where 169,040 barrels (26 875 m3) of −2 ° API (1 093 kg/m3) tar were recovered from a 5-acre (2 ha) pattern after injecting 1,847,500 barrels (293 730 m3) of steam(1). The second pilot test was conducted at the Saner Ranch from April 1981 to January 1983. A total of 133,260 barrels (21 190 m3) of tar was recovered from a 7.5-acre (3 ha) pattern after injecting only 1,069.000 barrels (169 950 m3) of steam(2). The main objective of the first pilot was to prove the feasibility of the FAST process for recovering −2 ° API (1 093 kg/m3) tar. The objectives of the second pilot test were to demonstrate the FAST process in a different part of the reservoir and to improve performance.

proposal was resubmitted in November 1975 and the project was initiated on. March 12, 1976 under the aegis of the newly formed ERDA Fossil Demonstration Plants Division. As part of the initial contract task schedule the BIGAS/SRC based 11 Clean Boiler Fuels froin Coal 11 conceptual process was selected as project base case flowsheet. Purdue University proceeded with data gathering activities for this process including meetings with representatives of the Pittsburgh & Midway Coal Company, the ERDA SRC contractor; the Bituminous Coal Research Laboratory, the BIGAS gasifier developer; PERC; IGT; Oak Ridge; the Bureau of Mines, Morgantown, and other relevant data sources. On J~ly 20, 1976 by letter from the contract technical representative, ERDA requested that the CBFC process be abandoned in favor of the conceptual process proposed by the Illinois Coal Gasification Group. This process had been presented to ERDA in response to an RFP for Pipeline Gas Demonstration Plants, and incorporated concepts tested during project COED, involved a proprietary COGAS gasification/combustion section, the proprietary Hail hydrotreating unit, as well as the RMP bulk methanation system. By letter dated August 2, 1976, Purdue University informed ERDA that the change was acceptable but that it would result in a four month delay in project time tables, assuming process data were released to Purdue by the end of August, 1976.-By ~-1ay of the following year such data were still not forthcoming because of complications in the negotiations between (now) DOE and ICGG. At that time, (Contract Amendment Dated 7/7/77 DOE requested, and Purdue agreed, to•~ndertake an additional task under the existing contract. This task involved the formulation of and literature

Regulatory affairs (RA) play crucial roles in the pharmaceutical industry because they are concerned with the lifecycle of healthcare products, they offer strategic, tactical, and operational direction, and they support working within the law to hasten the development and delivery of safe and effective healthcare products to people all over the world. The purpose of regulatory affairs is to create and implement a regulatory strategy to guarantee that the combined efforts of the drug development team result in a product that is acceptable to international regulators while also standing out from the competition. Microorganisms play a vital role in every field of drug such as production of antibiotics, antifungal, anticancer, vitamins, vaccines and enzymes etc. These are some examples where microbial products are widely used. In the present work we will discuss various aspects where microorganisms widely used in production of drug and their regulations in US and India.