TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractPublished analyses of well tests in gas-condensate reservoirs when pressure drops below the dew point are usually based on a two-zone radial composite model, representing regions of condensate drop-out around the wellbore and of initial gas composition away from the well. Laboratory experiments, on the other hand, suggest that three different mobility zones could exist: (1) an outer zone away from the well, with the initial liquid condensate saturation; (2) a zone nearer to the well, with increased condensate saturation and lower gas mobility; and (2) a zone in the immediate vicinity of the well with high capillary number which increases the gas relative permeability, resulting in a recovery of much of the gas mobility lost from condensate blockage. This paper investigates the existence of this latter zone in well test data. An example of well test analysis is discussed, which illustrates the difficulty of identifying such a zone as, in many cases, build-up and/or drawdown data are dominated by wellbore phase redistribution effects. Where the three zones can be identified, data are analyzed using a three-zone radial composite model to yield a complete characterization of the near-wellbore effects, and in particular the knowledge of the various components of the total skin effect: mechanical skin; rate-dependent two-phase skin; and skin due to gas condensate blockage. The existence of the three zones and the results of the analysis are verified with a compositional simulator where relative permeability depends on capillary number.
Despite the tremendous progress achieved in well test analysis in the last twenty years, many important and practical questions that are frequently asked by practicing engineers have received little attention in the literature. Three of these are addressed in this paper. The first one is whether it is possible to obtain more information from build-up data than from drawdown data in a testing sequence. By introducing a new definition of the radius of investigation - as opposed to the radius of drainage - based on the ability to interpret data using pressure derivatives, we show that the information obtainable from a long build-up following a short drawdown is actually limited by the gauge accuracy and noises as the shut-in time increases. The second frequently asked question (FAQ) relates to the minimum amount of detailed rate history which is required in order to obtain correct pressure derivatives, as a truncated or averaged rate histories may modify the derivative shapes at late times and therefore induce erroneous interpretations. A new rule of thumb is proposed, which combines the most recent flow-rate history with an effective time based on a fraction of the cumulative well production. The last FAQ concerns the possibility to distinguish a non-uniform mechanical skin effect from a uniform one from well test data. Current interpretations with fully penetrating wells yield a single value for the mechanical skin effect, which implicitly assumes that damage is uniform over the well surface. Various skin distributions are investigated with a multilayered model to determine how a non-uniform skin distribution around the wellbore affects the interpretation. It is shown that non-uniform skin distribution can be identified during specific flow-regimes and therefore must be taken into account in the interpretation. Introduction Very significant advances have been made in well test analysis over the last twenty years with the introduction of a systematic interpretation methodology, pressure derivative analysis and new interpretation models. As a results, well test analysis has not only become more powerful, but also easier and faster to perform. There remains, however, a number of issues which are faced by practicing engineers in their day-to-day work, but have not received much attention in the literature. This paper aims at giving some answers to these frequently asked questions (FAQ) in well test analysis. FAQ # 1: Can we see more in a build-up than in a drawdown? This has been a subject a disagreement for many years. Some defend the concept that once you start producing a well, the pressure disturbance is felt everywhere instantaneously, and therefore, by shuting the well in indefinitely, you should be able to obtain all possible information on the reservoir, even that which has not been obtained in the drawdown. Others believe that "if you don't see it in the drawdown, you don't see it in the build-up". The answer to the question can be obtained from the concept of the radius of investigation of a well test, which is the distance at which a given feature of the reservoir can be interpreted, taking into account the influence of noises in the data and the rate history of the test. Radius of drainage The radius of investigation, as defined in this paper, is different from the radius of drainage which is routinely used in well test analysis. The radius of drainage has been the subject of many publications, mainly in the 1950's and early 1960's (summarized by Van Poolen1) with a few more recent ones2–4. They all propose similar expressions, of the form reD=1+D.tD0.5 in dimensionless parameters4 In most cases, the use of the line-source solution with an infinitely small wellbore radius simplifies this equation to reD=D.tD0.5. A summary of the various definitions is given in Appendix A. Radius of drainage The radius of investigation, as defined in this paper, is different from the radius of drainage which is routinely used in well test analysis. The radius of drainage has been the subject of many publications, mainly in the 1950's and early 1960's (summarized by Van Poolen1) with a few more recent ones2–4. They all propose similar expressions, of the form reD=1+D.tD0.5 in dimensionless parameters4 In most cases, the use of the line-source solution with an infinitely small wellbore radius simplifies this equation to reD=D.tD0.5. A summary of the various definitions is given in Appendix A.
More than 40% of the world's conventional gas reserves are in reservoirs that contain significant amounts of H2S and CO2. The presence of these gases results in a number of challenges for the Field Development Plan (FDP). For a field with multiple fault blocks with unknown fault transmissivity, a key challenge is to understand the field connectivity and compartmentalization which impacts the ability to drain their reserves. This paper presents a comprehensive study to understand reservoir connectivity in a gas and oil fields located in South East Asia. This particular field has variation of the CO2 even in the same zone ranging from less than 10% to more than 80%wt. A key for production strategy and facility design is to be able to accurately quantify CO2 in each reservoir is. Initially, the CO2 study aimed to quantify the CO2 content for each reservoir using an advanced Downhole Fluid Analyzer (DFA), and then to use the DFA measurement as well as the available PVT data from nearby wells to understand reservoir connectivity through the use of a compositional gradient concept. Reservoir fluids that deviated from the compositional gradient were considered to not be in equilibrium. In addition, the use of a PVT thermodynamic calculation with a non-isothermal solution resulted in a possible identification of the CO2 charging location. Although the geochemistry study was conducted to understand the source of CO2 and hydrocarbon isotopes, it did not provide a conclusive result of the reservoir connectivity. As expected the hydrocarbon had a different charge source compared to the non hydrocarbon gases. Since the geochemistry study was inconclusive, a mass transportation simulation was performed to understand the reservoir connectivity and this information has had a great impact on understanding the production mechanism of this field. This paper provides a systematic process to understand the reservoir connectivity by using the integrated reservoir data such as pressure, DFA, PVT fluid properties, geochemistry, as well as the geological and geophysical interpretations of the reservoir. This paper offers an efficient way for reservoir characterization for proper field management for an important hydrocarbon discovery in South East Asia.
Gas condensate reservoirs exhibit a complex behavior when wells are produced below the dew point, due to the existence of a two-fluid system, reservoir gas and liquid condensate. Different mobility zones develop around the wellbore corresponding respectively to the original gas in place (away from the well), the condensate drop-out, and capillarity number effects (close to the well). Condensate drop-out causes a non-reversible reduction in well productivity, which is compensated in part by capillarity number effects. All these effects can be identified and quantified from well test data. Tests in condensate reservoirs, however, tend to be difficult to interpret. Build-up and/or drawdown data are usually dominated by wellbore phase redistribution effects and the main analysis challenge is to distinguish between reservoir effects, boundary effects, fluid behavior and wellbore phase redistribution perturbations. The paper compares theoretical well test behaviors in vertical and horizontal wells as obtained from compositional simulation with actual behaviors selected from more than twenty different gas condensate reservoirs. An interpretation methodology is described, which uses time-lapse analyses, deconvolution and different analytical and numerical tools to identify the probable causes of the pressure data behavior: two-region and three-region analytical composite models to represent the various mobility zones around the wellbore; a voronoi-grid numerical simulator to represent discontinuous boundaries; a multilayered analytical simulator to account for the geological description and a compositional simulator to verify the fluid behavior. It is shown that, in addition to the usual well test analysis results, it is possible to obtain parameters required for reservoir simulation and well productivity forecasting, such as gas relative permeabilities at the end point, critical oil saturation, and the base capillary number. Introduction Gas condensate reservoirs are becoming more common as deeper depths are being targeted in the exploration for oil and gas. The behaviors of such systems are complex and are still not fully understood, especially in the near-wellbore region. Well tests, in particular, are difficult to interpret. A discussion of the state-of-the-art in gas condensate well test interpretation was published in 2000 by Gringarten et al.[1] with an extensive review of the related literature. To summarize, a characteristic of gas condensate production is the creation of a condensate bank when the bottomhole pressure drops below the dew point[2] pressure. This reduces the gas relative permeability[3] around the well and leads to a loss of well productivity,[4–7] with some wells even ceasing production completely due to condensate loading in the wellbore.[5] This "condensate banking" effect, however, is compensated by "velocity stripping" which increases the gas mobility in the immediate vicinity of the wellbore.[8] "Velocity" or "viscous" stripping (also called "positive coupling")[9–13] occurs at high capillarity number, a dimensionless parameter that represents a ratio of viscous to capillary forces:[14,15]
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