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Downhole casing leaks in oil and gas wells will highly impact the shallow water horizons and this will affect the environment and fresh water resources. Proactive measures and forecasting of this leak will help eliminate the consequences of downhole casing leaks and, in turn, will protect the environment. Additionally, downhole casing leaks may also cause seepage of toxic gases to the fresh water zones and to the surface through the casing annuli. In this paper, we introduced a risk-based methodology to predict the downhole casing leaks in oil and gas wells using advanced casing corrosion logs such as electromagnetic logs. Downhole casing corrosion was observed to assess the remaining well life. Electromagnetic (EM) corrosion logs are the current practice for monitoring the casing corrosion. The corrosion assessment from EM logs is insufficient because these logs cannot read in multiple casings in the well. EM tool gives average reading for the corrosion in the casing at a specific depth and it does not indicate the orientation of the corrosion. EM log does not assess the 360 deg corrosion profile in the casing and it only provides average value and this may lead to wrong decision. All of this makes EM logs uncertain tools to assess the corrosion in the downhole casing. A unified criterion to assess the corrosion in the casing and to decide workover operations or not has been identified to minimize the field challenges related to this issue. A new approach was introduced in this paper to enhance the EM logs to detect the downhole casing corrosion. Corrosion data were collected from different fields (around 500 data points) to build a probabilistic approach to assess the casing failure based on the average metal loss from the EM corrosion log. The failure model was used to set the ranges for the casing failure and the probability of casing failure for different casings. The prediction of probability of failure (PF) will act as proactive maintenance which will help prevent further or future casing leaks.
Downhole casing leaks in oil and gas wells will highly impact the shallow water horizons and this will affect the environment and fresh water resources. Proactive measures and forecasting of this leak will help eliminate the consequences of downhole casing leaks and, in turn, will protect the environment. Additionally, downhole casing leaks may also cause seepage of toxic gases to the fresh water zones and to the surface through the casing annuli. In this paper, we introduced a risk-based methodology to predict the downhole casing leaks in oil and gas wells using advanced casing corrosion logs such as electromagnetic logs. Downhole casing corrosion was observed to assess the remaining well life. Electromagnetic (EM) corrosion logs are the current practice for monitoring the casing corrosion. The corrosion assessment from EM logs is insufficient because these logs cannot read in multiple casings in the well. EM tool gives average reading for the corrosion in the casing at a specific depth and it does not indicate the orientation of the corrosion. EM log does not assess the 360 deg corrosion profile in the casing and it only provides average value and this may lead to wrong decision. All of this makes EM logs uncertain tools to assess the corrosion in the downhole casing. A unified criterion to assess the corrosion in the casing and to decide workover operations or not has been identified to minimize the field challenges related to this issue. A new approach was introduced in this paper to enhance the EM logs to detect the downhole casing corrosion. Corrosion data were collected from different fields (around 500 data points) to build a probabilistic approach to assess the casing failure based on the average metal loss from the EM corrosion log. The failure model was used to set the ranges for the casing failure and the probability of casing failure for different casings. The prediction of probability of failure (PF) will act as proactive maintenance which will help prevent further or future casing leaks.
During transient tests, both pressure and temperature change depending on downhole flow rate. In gas producing wells, Joule-Thomson cooling and frictional heating effects are the main dynamic factors that cause flowing bottomhole temperature to differ from the static formation temperature at that depth. When a gas well is shut in, JT cooling effect is vanished and this causes a sudden sharp increase in sandface temperature. Then as the effect of wellbore storage ends, wellbore temperature gradually cools down due to heat conduction with near wellbore region. This paper demonstrates the applications of temperature transient data and proposes a new technique for using temperature transient data in gas wells in order to determine end of wellbore storage. Also, the effects of permeability and well productivity on temperature behavior are discussed. Three field examples are shown in which both temperature and pressure transient data were analyzed for more accurate welltest interpretation. This paper shows how knowledge of Joule-Thomson cooling effect and frictional heating effect can be applied for reservoir characterization. Introduction In pressure transient tests, the early portion of the well test data is usually affected by the wellbore storage effect and can be influenced by skin and reservoir permeability. Many analysts rely on pressure derivative curve to diagnose wellbore storage period and radial flow regime on pressure transient data. However, there are field examples that flow regimes can't be accurately determined. The wellbore storage effect delays the formation pressure response and distorts the early portion of pressure transient data. Diagnosing of the radial-flow regime is crucial to quantitative interpretation since it provides values for permeability and skin. Unit slope and the plateau on the pressure derivative curve as well as Horner plot are usually used to identify pure wellbore storage and radial flow regime as shown on Fig.1. The interpreter's first task always is to identify the unit slope line and derivative plateau to identify flow regimes. Since different factors including wellbore storage, skin and reservoir heterogeneity affect pressure response, detecting end of wellbore storage and flow regimes might have uncertainties. Horizontal wells, for example, pose two special problems for the reservoir engineer. The first is the unavoidably large wellbore storage effect as horizontal section may extend for thousands of feet and cannot be isolated from the transient. The second is the more complex nature of transient, which makes diagnosis more difficult. So wellbore storage may distort the early time flow regimes and cause uncertainty in detecting first plateau on derivative curve. Therefore, determining accurate time at which wellbore storage stabilizes, has a significant impact on the analysis and interpretation of pressure data.
Long (horizontal) completion intervals typically show a wide variation in the inflow distribution along their length due to either formation heterogeneity or (frictional) flow pressure losses. Monitoring of the inflow profiles in such wells is an important step in efficient reservoir management. Accurate temperature measurements (using distributed temperature sensors, permanent downhole gauges or other forms of production logging) have become more widely available in recent years. Many published papers describe temperature sensing and its phenomenological interpretation; but few attempts have been made recently to develop a comprehensive mathematical basis for the analysis of downhole temperature behaviour.This paper presents a holistic, analytical, mathematical model for calculation of the temperature profile in horizontal wells producing liquids for reservoirs where thermal recovery methods are not being employed. The model presented in this paper rigorously accounts for (1) the Joule-Thomson effect, (2) convection, (3) transient fluid expansion and (4) time-dependent heat loss to the surrounding layers.A synthetic horizontal well model has been built using a commercial, scientific simulator as a test-bed to provide the data to allow a rigorous evaluation of the efficacy of our novel analytical methods. Asymptotic, analytical solutions have also been found for transient and steady-state flow. It has also been found possible, in addition to these constant flow rate solutions, to apply the well known pressure analysis solution techniques for the estimation of (1) thermal properties and (2) inflow profiling.The methods proposed here can be applied to a wide variety of well completion types, flow conditions and system properties. They form the basis for the calculation of oil and water flow phase cuts and distributions based purely on temperature measurements. Their use will further increase the potential applications of the modern downhole monitoring and control capabilities currently being installed in wells. As such, they will form an essential element of the "digital oil field".
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