In 1999, an oilfield experiment was initiated to test the application of electrical measurement technologies to permanent reservoir monitoring. The principal objective of the experiment was to demonstrate the feasibility of monitoring water movement between an injection and an observation well. This paper describes the interpretation of the data provided by the resistivity arrays and discusses the data quality and reliability of the measurements.Two wells were drilled into the Mansfield sandstone reservoir in Indiana, U.S.A. The D-8 injector well was located in the center of four development wells. The OB-1 monitoring well was offset 233 ft to the southwest in a location midway between the D-8 injector and the No. 3 production well. The injector was instrumented with a 16-electrode resistivity array that was run on the outside of insulated casing and cemented into the annulus of the well. A similar array was cemented into the annulus of the monitoring well.In March 1999, the D-8 well was perforated and acidized. A surface gauge was used to monitor injection rates and pressures. Initially, injection proceeded at a rate of approximately 20 B/D, increasing to 90 B/D after fracture stimulation. The D-8 array records responses to wellbore operations and injection. It clearly distinguishes the movement of the waterfront in different zones. The OB-1 electrical array clearly indicates early water breakthrough by means of an induced fracture. The data show good signal-to-noise ratio and high reciprocity.The experiment has demonstrated the viability of using permanently installed resistivity arrays to monitor the movement of oil/ water contacts and salinity fronts that are some tens of feet away from the wellbore. Results demonstrate the feasibility of using such arrays to monitor oil/water contact movements remote from injection, monitoring, and production wells.
Summary This paper presents a procedure for interpreting data acquired with permanent downhole pressure sensors in association with surface or downhole rate measurements. The usefulness of this data source in reservoir description and well performance monitoring is illustrated. Unlike previously published examples, the interpretation is based on the analysis on a stream of data acquired over large periods of time, thus utilizing the continuous nature of the measurements. Three field cases are presented using the pressure and rate data in decline-curve analysis for wells with a variable downhole flowing pressure, and through more sophisticated models that are similar to the ones used in well test analysis. Because such interpretation is conducted while continuing production, it is particularly well suited for a well or group of wells under extended testing, which are equipped with downhole gauges and are flowing through surface separation and metering systems. Wells completed with both permanent downhole rate and pressure measurements are also ideal candidates for this type of analysis. Finally, the influence of the pressure sensor long term drift and the rate measurement error on the interpretation results and future forecasts are investigated. Introduction Since the first permanent downhole gauge installations in the early 1960's on land wells, the new technology in cable manufacturing, gauge sensor and electronics has permitted reliable installations also in hot, deep wells and subsea completions. These systems have gained acceptance among operators, and currently several hundred downhole gauges are installed every year. The traditional applications associated with permanent downhole systems can be characterized by four distinctions:single well optimization,reservoir description,safety improvement, andoperating cost reduction. Combining the recent technology development and these applications, the downhole gauge installations can be safe and reliable, as well as good investments. Most of the previous papers on the subject have focused on the hardware involved in permanent downhole pressure gauge installations. Regarding reservoir description, a few examples have been published where data recorded by the permanent downhole gauges have been used in well test transient analysis and multiwell interference tests. However, little has been published on the use of continuous downhole measurement in order to enhance reservoir description when associated with rate data during the pseudosteady state or depletion period of a field or a separate block. Decline curve analysis is one of the most widely used and documented methods for reserve estimation and production forecasting for a field under depletion. Solutions have been published for the case of a well producing at constant downhole flowing pressure. In reality, due to production constraints or change in operating procedures, the downhole flowing pressure seldom remains at a constant level over long periods of time. In the decline curve analysis literature, various methods have been proposed to account for these pressure variations; these include normalization and various types of superposition based on the pressure change observed at the wellhead.
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In 1999 an oilfield experiment was initiated to test the application of electrical measurement technologies to permanent reservoir monitoring. The principal objective of the experiment was to demonstrate the feasibility of monitoring water movement between an injection and observation well. This paper describes the utility of the data provided by the resistivity arrays and discusses data quality and reliability of the measurements. Two wells were drilled into the Mansfield sandstone reservoir in Indiana. The D-8 injector well was located in the center of four development wells. The OB-1 monitoring well was offset 233 ft to the southwest in a location midway between the D-8 injector and the No. 3 production well. The injector was instrumented with a 16-electrode resistivity array that was run on the outside of insulated casing and cemented into the annulus of the well. A similar array was cemented into the annulus of the monitoring well. In March, the D-8 well was perforated and acidized. A surface gauge was used to monitor injection rates and pressures. Initially, injection proceeded at a rate of about 20 B/D, increasing to 100 B/D after fracture stimulation. The D-8 array records responses to perforation, acidization, swabbing, fracturing, and injection. It clearly distinguishes the movement of the waterfront in different zones. The data show good signal-to-noise ratio and high reciprocity. The OB-1 electrical array clearly indicates early water breakthrough via an induced fracture. The arrays show no degradation of signal over the 17-month duration of the experiment. The experiment has demonstrated the viability of using permanently installed resistivity arrays to monitor movement of oil-water contacts that are some tens of feet away from the wellbore. Results demonstrate the feasibility of using such arrays to monitor oil-water contact movements remote from injection, monitoring, and production wells. Introduction The industry drive toward using intelligent wells to improve recovery efficiency will require continuous monitoring and optimization of reservoir drainage. Currently, commercial monitoring is through sensors that measure flow in the wellbore and permanent borehole pressure gauges. These sensors allow for reactive reservoir management: opening or closing production zones as a response to breakthrough of unwanted fluids into the wellbore. Proactive reservoir management is possible if we are able to detect the advance of unwanted fluids in the formation, prior to their breakthrough into the production stream. We have conducted an oilfield experiment to demonstrate that sensors can be deployed and used to monitor fluid movement remote from the wellbore.1 As this was the primary objective of the experiment, emphasis was placed on demonstrating the feasibility and utility of such measurements, rather than on testing a commercially viable deployment scheme.
Summary Optimization of hydrocarbon recovery requires information on the space and time behavior of the saturation of various fluids present in the reservoir. This is particularly true for oil fields under secondary recovery such as waterflooding, where an even reservoir sweep or zones of bypassed oil can be assessed by a proper description of the waterfront advance. Recently, permanent downhole electrodes have been deployed successfully in oil wells. This technology allows the time variation of the electrode potentials to be interpreted in terms of changes in saturation within the formation. However, the depth of investigation of such measurements is limited. Time-lapse pressure transient is an independent source of information with a greater depth of investigation and, therefore, it provides an adequate complement to the permanent resistivity array measurement. In this paper, we propose to use pressure buildup from repeated shut-in in association with the electrical measurements. After recalling analytical analogies in both types of measurements, we propose a quick-look method for interpreting the time-lapse pressure transients. We then compare the physical and practical advantages of each type of measurement and the domain of application of the two measurements with respect to fluid and reservoir properties. Finally, we propose an example showing the benefit obtained by coupling the two techniques.
In this paper, we first provide guidelines for selecting the most appropriate permanent downhole sensor or combination of sensors for reservoir monitoring, given fluid and rock characteristics. This selection is applied to pressure, electrical, and seismic sensors, based on their respective response equations to formation and rock properties. We then present two synthetic cases illustrating the interpretation of permanent monitoring data, with emphasis on the benefits of data fusion and data assimilation, referring respectively to the use of multisensor and time-lapse data; more specifically, we show how those approaches enhance the convergence of the inversion process towards the solution. Introduction One important challenge for reservoir management in the coming decade is to monitor fluid movements in hydrocarbon reservoirs, with the goal of optimizing their drainage. Three main physical principles can be envisaged: resistivity, pressure response to well tests, and acoustics (or seismics), since changes in resistivity, mobility, and elastic properties are expected at a front location in a hydrocarbon reservoir. To this end, permanent downhole sensors such as pressure gauges, electrode or geophone arrays have therefore been1 or are currently being developed. Arrays of such sensors would allow repeatedly conducting reservoir surveys around the instrumented wells. Because different tools are sensitive to different reservoir and fluid properties, sensor-screening criteria have to be established to take the full benefit of investing in such a technology. This is dealt with, in this paper, by proposing a simple graphical method that will help in choosing the optimal single sensor or the combination of sensors best suited to a given problem and environment. Once the selected sensors have been deployed, interpreting the data recorded by the sensors to obtain information on the fluid movement within the reservoir requires an inversion process. This inversion process can be improved by taking advantage of time-lapse acquisition (i.e., data assimilation2) and/or by the concurrent use of different types of sensor (i.e., data fusion3). In this paper, two synthetic examples are used to illustrate the use of permanently acquired data in a waterflood characterization context. The first example deals with the determination of a water-injection front movement from a simultaneous inversion of pressure, electrical potential, and seismic data, showing how their joint use can alleviate the indetermination on the front geometry parameters to be inverted. In the second example, we show how information about relative permeabilities can be derived from interpreting a continuous stream of flow rate and electrode-array potential data. In particular, we show how the time-lapse nature of the acquisition can be used to obtain better parameter estimates. Sensor Response Equations Selection of a wellbore sensor, such as a rate measurementdevice, is relatively straightforward, given the anticipated multiphasic well production and the device's nominal characteristics. By contrast, selecting one (or several) reservoir sensor(s) may be a much more difficult task, given the large number of reservoir and fluid properties that are influencing the measurement(s). One should therefore return to the response equation of each sensor to evaluate the sensitivity of a particular measurement to a given set of reservoir parameters. The following equations correspond to the response of resistivity, seismic, and pressure sensors for the situation depicted in Fig. 1; i.e., the simple case of a vertical water-front movement across a homogeneous oil-bearing reservoir. The sensors are located in the producing well, and the distance between the sensor and the front at time? is L(t).
Cores, open hole logs, formation testers, pressure transient tests, and production logs are usually used to assess reservoir heterogeneity. A common limitation of these techniques is that they do not provide two-dimensional spatial information of reservoir characteristics. For example, cores and logs have excellent vertical resolutions, but very small lateral radii of investigation, and the pressure transient tests have a large lateral radius of investigation, but very poor vertical resolution. Constructing an appropriate simulation model requires rescaling the data, and that may introduce significant uncertainties. To address these limitations, we explored the use of electrode resistivity array (ERA) measurements in a carbonate formation for reservoir characterization. The ERA was installed on tubing in a barefoot well rather than permanently cemented outside the casing as in previous applications. This notable difference introduced particular issues in the ERA data acquisition and interpretation, but also provided flexibility for device installation and operation. Furthermore, the ERA measurements were carried out in conjunction with low-salinity water injection and production in the same well. It was found that the ERA voltages near a source electrode showed unique characteristics that represented local formation heterogeneity. Although the new technology can be used at any scale, the focus was on characterizing formation heterogeneity within the length of the ERA string in the vertical direction and about 100 ft laterally around the wellbore. The scale of the investigated formation heterogeneity is comparable to grid sizes used in current reservoir simulations. Models were developed to identify stratified permeability heterogeneities from the time-lapse ERA voltages. The stratified heterogeneity estimated from the ERA measurements was compared to and verified by open hole logs and core analyses. The final heterogeneous reservoir model from ERA was subsequently applied to a numerical simulation that integrated the dynamic fluid flow, salt transport, and electrode array responses for water front monitoring and multiphase formation property evaluation and confirmed the first pass estimates of the identified heterogeneities. Introduction Permeability heterogeneity, especially that induced by formation stratification, is very important in all aspects of reservoir engineering processes, from well placement to enhanced oil recovery applications. The stratified and interwell heterogeneities dictate fluid movement and waterflooding efficiency, thus significantly affecting hydrocarbon recovery. This is particularly true in carbonates, for which reservoir heterogeneity exists at many different scales. Detailed reservoir characterization is needed to better map the formation heterogeneity for reservoir management. Core experiment, open hole wireline logging, wireline formation tester, pressure build up, injection/fall off test, and production logging are the conventional methods for characterization of reservoir heterogeneity. Although applications and advantages of these techniques in formation evaluation are well established, each has limitations that should not be overlooked. In general, these measurements can be divided into two categories: static and dynamic.
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