Early in 1964, Pye and Sandiford established the fact that polymer flooding can result in greater oil recovery than the conventional water flooding. Many additional papers sustaining and extending this information have since appeared in the literature. In the past forty years, many field-scale polymer flooding projects have been put into production and lots of information has been available from which to draw conclusions regarding of lessons learnt and experiences gained on field-scale polymer-flooding. The purpose of this paper is to examine the ranges of some important parameters within which successful polymer flooding has been achieved and to present lessons learnt and best practices on polymer flooding, thus direct to design and further achieve a high-performance polymer-flooding project. Introduction Mechanisms of Polymer Flooding In the reservoir, oil and water are immiscible fluids. As a result, neither one can completely displace the other in the subsurface condition. This is reflected by the non-zero irreducible water (Swir) and residual oil saturation (Sor) on an oil-water relative-permeability curve. In the lab, no matter how large volume of water has been injected into a core, the oil saturation will never be lower than Sor only by the conventional water flooding. However, it has been known for many years that the efficiency of a water flooding can be greatly improved by lowering the water-oil mobility ratio in the system. Such a change may lead to better sweep efficiency and also to more efficient oil displacement in the swept zone. By adding of suitable polymer solutions to injected water, the water mobility can be reduced and oil recovery increased as shown in Figure 1. During polymer flooding, a water-soluble polymer is added to the injected water in order to increase water viscosity. Depending on the type of polymer used, the effective permeability to water can be reduced in the swept zones to different degrees. It is believed that polymer flooding cannot reduce the Sor, but it is still an efficient way to reach the Sor more quickly or/and more economically. According to Riley B. Needham[2], polymer solutions may lead to an increase in oil recovery over that from a conventional water flooding by three potential ways:through the effects of polymers on fractional flow,by decreasing the water/oil mobility ratio, andby diverting the injected water from zones that have been swept. The above three effects can make the polymer flooding process more efficient. Early pilot studies on polymer flooding can be traced back to 1944. Detling[3] (Shell Development Co.) obtained a U.S. patent covering the use of several additives for viscous water flooding. His objective was to increase the viscosity of the flooding water and then to improve water-oil mobility ratios. During the next two decades, many studies[4–13] have shown up like mushrooms and many patents have been granted covering specific water-soluble polymers or specific conditions of viscous water flooding in the world.

The application of interwell tracer tests is becoming increasingly important to the petroleum industry. Interwell tracer tests, as a proven and efficient tool, have been used to investigate reservoir flow performance and reservoir properties that control gas and water displacement processes. Tracer data have been used to reduce uncertainties attributed to well-to-well communications, vertical and horizontal flow, and residual oil saturation. This paper describes the development of interwell tracer tests in the petroleum industry, from the first qualitative tracer test in the 1950s to the latest quantitative tracer test in the 2000s. The results of our study indicate that poor sampling is the most frequently encountered problem that leads to a failure tracer test and only a small number of interwell tracer tests have employed the advanced numerical modeling methods to analyze the test data. In addition, the interwell tracer tests in the petroleum industry are not well studied as hydrology industry. Therefore, the interwell tracer tests interpretation methods deserve to be paid more attention, so that petroleum engineers can take better advantage of the costly interwell tracer tests. Introduction Although tracer tests[1] were developed for tracking the movement of groundwater in the early 1900s, they were neglected by the petroleum industry until mid 1950s.At this time, petroleum engineers[2,3] started to conduct tracer tests for determination of flow of fluids in waterflooded reservoirs. In the petroleum industry, solvent is sometimes injected into oil or gas bearing formations for the purpose of producing more hydrocarbons. Tracers can be added to the injected solvent to determine where the injected solvents go. The subsurface flow in the reservoir is anisotropic, and the reservoirs are usually layered with significant heterogeneity. As a result, solvent movement in the reservoir is difficult to predict, especially in reservoirs containing multiple injectors and producers. However, the flow paths can be identified by tagging solvent at each injection well with a different tracer and monitoring the tracers appearing at each producing well. Therefore, multiple tracers are often used for interwell tracer tests in the petroleum industry. Interwell tracers can provide information on flood patterns within the reservoir. This information is reliable, definitive and unambiguous, thus it helps reduce uncertainties about flow paths, reservoir continuity and directional features in the reservoir. Therefore, petroleum engineers can obtain information on reservoir continuity from the amount of each tracer produced from each well.Reservoir barriers can be identified by non-recovery or delayed recovery of specific tracers. At the same time, tracer test data can help determine residual oil saturation. Tracer test results also provide information on fracture characteristics in a naturally fractured reservoir. However, interwell tracer tests are considerably time-consuming and they must last long enough (from several days to several weeks or even months) for injected tracers to flow from injectors to producers. The interwell tracer tests have been applied in many fields across the world. The majority of the fields are located in the North America and Europe. This study gives a review of the development of inter well tracer tests as it is found in the open literature search in the petroleum industry. Unfortunately, not all field tests are adequately described and this review is limited to the publicly accessed papers. The scope of this review is interwell field tracer tests and studies in the petroleum industry. Consequently, experimental works and theoretical studies on interwell tracer flow are not included in this study. Although single well tracer tests are useful for the determination of residual oil saturation, they are also excluded from this review.

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Background. Identifying the locations and amounts of unproduced gas in mature reservoirs is often a challenging problem, due to several factors. Complete integrated reservoir studies to determine drilling locations and potential of new wells are often too time-consuming and costly for many fields. In this work, we evaluate the accuracy of a statistical moving-window method (MWM) that has been used in low-permeability (“tight”) gas formations to assess infill and recompletion potential. The primary advantages of the technique are its speed and its limited need for data, using only well location and production data. Method of Approach. To test the method, we created a number of hypothetical reservoirs and calculated infill well potential using a reservoir simulator. We used the MWM to analyze these data sets, then compared results to those from the reservoir simulations. Results. The results validate empirical observations made using MWM during field evaluations. Depending on the level of reservoir heterogeneity, the MWM infill predictions for individual wells can be off by more than ±50%. The MWM more accurately predicts the production potential from a group of infill candidates, the MWM, however, more often to within 10%. We describe a procedure to estimate the number of wells needed to predict production potential to within a stipulated accuracy. The ability of MWM to accurately predict production performance for groups of wells shows that it can be a useful tool for scoping studies or identifying areas for more detailed evaluation.

TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractWavelet is first introduced by Alfred Haar in 1910, but the development of wavelet was very slow until the middle of 1980s. In 1984, Jean Morlet made the wavelet rebirth by developing a new way of analyzing the seismic signals to overcome the deficiencies in the Fourier method. Since then, the new developments of wavelets have fascinated the scientific and engineering communities.A wavelet is a waveform of effectively limited duration that has an average value of zero and wavelets are a family of basis functions, which can separate a signal into distinct frequency packets that are localized in the time domain. Thus, wavelets are well suited to analyze nonstationary data. They can smooth the basic signals and keep the details of basic signals. Therefore, they provide a multiresolution framework for data representation.Wavelet analysis is a rapidly developing area in many disciplines of science and engineering and it is used in a wide variety of applications in the areas of medicine, biology, data compression, etc. In recent years, wavelet analysis has found its application in the petroleum industry. This paper reviews the recent application of wavelet analysis in the industry.Various application examples are discussed, especially the examples in the areas of reservoir characterization, geological model upscaling, and well testing. simple digital filter ideas, shown in Fig.1. Thanks to Daubechies' work, wavelet transform has been widely used in many fields such as pattern recognition, image compression, mechanical fault diagnostic, signal de-noising, signal compression, earthquake diction, and other areas since 1990s.