Saudi Aramco's Ghawar Field is a massive carbonate reservoir with sub-zones of varying reservoir quality and has been under flank-water injection. It is a complex reservoir, with thin super permeability layers (10 feet) that are generally stratiform and in some cases fractured, associated with high productivity. Laterally extensive super permeability beds, in good vertical communication with the rest of the oil bearing reservoir, can significantly increase both well productivity and sweep efficiency. However, isolated super permeability layers can cause early water breakthrough, which adversely affects oil recovery as well as increases the field operational cost. Furthermore, large permeability contrasts can complicate effective drainage of lower porosity zones in the lower part of the reservoir that contains about 35 % of the original oil in place. For this field, pressure and saturation monitoring have been key factors in achieving the overall reservoir management objective of maximizing recovery at the lowest cost. Saudi Aramco is currently surveying the key new wells drilled behind the flood front using the multi-probe formation tester for obtaining pressure measurements, performing interval tests, and taking fluid samples along the well-bore. The primary objective of the surveys is to establish whether the super permeability beds as well as the lower porosity zones are introducing differential pressure depletion, which will directly impact the field's completion and production strategy. Obtaining fluid samples across the reservoir zones is also a key part of the surveys, to establish water salinity and movable oil fraction in zones with breakthrough where the injection and formation waters are mixed. Determining the fraction of movable oil in the lower porosity zones, where the conventional open-hole log results are uncertain, is very crucial in optimizing recovery. It is also a powerful method to evaluate the sweep in the lower zones matrix where the diffused fractures density is higher and assist the dynamic interaction between the two systems. The on-going Uhawar Field monitoring has shown that there is good vertical communication in the higher quality zones, at the top of the reservoir and embody the super- permeability thin beds. However, local and reservoir scale barriers as well as differential depletion has been observed towards the base of the reservoir. These barriers have resulted in poor sweep efficiency with zones containing bypassed oil. These zones are now being targeted by dedicated dual vertical-horizontal completions. In this paper, we show that the pressure and saturation monitoring integrated with other dynamic and geological data contribute immensely to obtain the best completion for optimizing oil production and recovery. Furthermore, we also show that in areas of good vertical communication, super permeability is advantageous to the field development, due to its high productivity and large drainage area exposure. P. 111
The original gas lift valve testing method which has been proposed by South West Research Institute, SWRI, is very slow and expensive. The current API testing method is based on the API RP 11 V2 procedure. This testing method is not sufficient for all the gas valves purposes. On the other hand, the gas valves just calibrated at the manufacturer based on the API code which may not satisfy the application at all because the calibration is in static conditions whereas the valve is working under dynamic modes. Application of this work is to test and calibrate the gas valve based on the best performance and efficiency at the wellbore location. This method which is based on concept of pressure decay is really unique, novel, and inexpensive. It can be carried out at the wellbore location. This method is able to determine the actual flowing area, stem travel, discharge coefficient, and load rate of valve during flowing conditions. The significant section is that this method will correct the API standards of calibrating for different applications which is a great progress in this field of action. Introduction Artificial lift comes to the play when the production of oil (formly water) is not done through natural well flow. Blow down can be useful for low water-cut systems.1 Gas lift often can enhance the low GOR reservoir performance. Apparently, with increasing GOR, gas lift becomes less effective. So, the need for gas lift is related to the GOR prediction. Gas lift is performing useful in deep water with long offset flowlines. The reason is because of reducing the chance of slug formation. The reason behind it is because of severe slugging occurrence the relatively low production rates which make the gas lift a must at the beginning. Blowdown technique is more limited in downhill flowlines rather than uphill flowlines. In this system gas is continuously injecting through the casing or tubing and push the pass through some valves located in designated places and lift the volume of the liquid above. In this process, the gas lifts a slug of liquid each time. Setting the gas lift valves, GLV, is critical to the production. The GLVs should be set based on their initial opening pressure decreasing from surface level to the sandface, meaning when the top valve is getting ready to open; all the valves below are open. Selecting the GLVs port sizes and the distance between them as well as the initial opening pressure of each valve should be calculated and adjusted accurately to get the aimed results. The GLV is the most important component in such a design. The nitrogen-charged bellow pressure in the GLV may changes due to the temperature change from the surface to the bottomhole which should get calibrated and corrected before each installation for the best performance. Valve Performance Models There are a lot of attempts has been carried out throughout this mean. Some works 1 tried to bring a statistical modeling to predict the gas passage through the valve but some apparatus errors never let that go through. Correcting the facility error by another fellow 2 ended up to a correlation. This paper 2 proposed a criterion based on test rack opening pressure, Ptro, to differentiate between orifice and throttling flow. Eq. 1 and Eq. 2 bring the developed correlation for gas passage through orifice flow and throttling flow respectively.
Integration of well test results, horizontal well information, bore hole imaging, see Figure 1, 3-D seismic, and coherency analyses has made possible the ability to locate and define vertical faults and fractures. Fracture orientation, Figure 2, based on image log data from several wells, can increase our understanding of how the direction of these fractures effects reservoir performance. Conductive faults and fractures that contribute to fluid flow, along with stratified high permeability regions, must be included in our mathematical models.
Volumetric methods are used to estimate the hydrocarbons in place of a reservoir. They require petrophysical data including porosity ø and water saturation Sw which cannot be directly measured but must be inferred from other measurements. For example, water saturation is conventionally obtained from the Archie's equation, which requires inputs of porosity, ø, cementation factor, m, tortuosity factor, a, saturation exponent, n, true reservoir resistivity, Rt, and resistivity of formation water, Rw. Uncertainties in these input values directly affect the accuracy of water saturation estimation. In this paper, we investigate the propagation of uncertainties of these input parameters into Sw estimated by Archie's equation. Error propagation equations (based on a Taylor series expansion of Sw around the mean values of the input parameters) are derived for uncertainty characterization. Two cases are considered for the relationship between the input parameters; correlated or completely independent. It is shown that correlation among the input parameters, which may be due to different rock facies, can increase or decrease uncertainty in Sw and hence, ignoring existing correlation among the input parameters may lead to incorrectly characterizing the uncertainty in Sw. In addition, the dimensionless sensitivities and relative uncertainties of the input parameters, derived from the error propagation equations, clearly identify which of the input parameters will dominate the total uncertainty in Sw computations. Monte Carlo methods were used to verify the developed error propagation equations. A comparative study shows that the error propagation method is a good first approximation for uncertainty analysis, especially if the resulting Sw distributions are normal. However, it is well known that Monte Carlo methods are more general as they provide rigorous sampling of the response function (Sw in our problem) by accounting for the nonlinearity existing between the response function and its input parameters, and thus should be used for accurately quantifying the uncertainty. Introduction Uncertainties in petrophysical properties are widely accepted, but rarely applied in formation evaluation and reservoir characterization. Without proper consideration of these uncertainties, estimation of original oil in place (OOIP) can be in error (Cronquist 2001). This is particularly important for reservoirs with large reserves, such as those super giant fields in the Middle East. In order to calculate water saturation from Archie's equation (Archie 1942), the porosity, f, cementation factor, m, tortuosity factor, a, saturation exponent, n, true reservoir resistivity, Rt, and resistivity of formation water, Rw, are needed. These input values have uncertainties associated with them, which will result in an uncertainty in the estimated Sw. Main sources of uncertainty in the determination of porosity from well logs are measurement errors, selected models, and uncertainties in input parameters related to the models (Verga et al. 2002; Adams 2005). The parameters m and n are normally obtained from electrical measurements made on core plugs. For microscopically heterogeneous media, particularly carbonates, expressions for m have been derived in the literature in terms of the intragranular and vuggy components (Ramakrishnan et al. 2001). Changes in the cementation factor, m, and saturation exponent, n, are often difficult to quantify (Eyvazzadeh et al. 2003). The uncertainties in m and n will propagate into the uncertainty in Sw. Rt must be determined from log data, and quantification of uncertainties in Rt may be difficult. Rw is one of the most difficult variables to obtain and may have a high degree of uncertainty. Eyvazzadeh et al. (2005, 2007) demonstrate how the errors in saturation values can be calculated based on the resistivity measurements. The parameters in the Archie equation such as f, m, n, Rt, and Rw may be associated with high levels of uncertainty. Generally, petrophysical interpretations do not account for uncertainty thus decisions made based on deterministic values may result in improper engineering decisions such as design of facilities.
This reference is for an abstract only. A full paper was not submitted for this conference. Abstract Reservoir heterogeneity, single and multi-phase formation properties dictate well productivity, reservoir performance and management strategy. Cores, open hole logs, formation testers, pressure transient tests, and production logs are usually used to estimate the reservoir heterogeneity and quantify the single and multi-phase formation properties. The results obtained from these techniques are utilized in reservoir simulations to assess the reservoir performance and optimize the reservoir production. A common limitation of these measurement 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. Directly using the results from these measurements in reservoir simulations is difficult because of scale mismatch between the measurements and the requirements in a typical simulation model. Constructing an appropriate simulation model requires rescaling the data, and that may introduce significant uncertainties. This paper presents a comprehensive reservoir characterization method for a Middle East carbonate reservoir through integrating open-hole logs, wireline formation tester results, a series of pressure buildup, stepwise water injection and falloff tests, Electrode Resistivity Array (ERA) measurements and single well simulations. The results obtained in this study represent much larger lateral formation volume than cores and open-hole logs and have a similar vertical scale as a reservoir simulation. The primary objectives of the intentionally established two-phase flow condition wereto allow effective measurements from a specially designed Electrode Resistivity Array;to calibrate a multilayer reservoir model, which was obtained using openhole logs and formation tester results, on a scale that was suitable for reservoir simulations using the ERA measurements; andto estimate effective permeabilities at original connate water conditions as well as the final remaining oil saturation conditions. The testing system included the ERA string and set at the top 120 ft of the production zone, a permanent downhole pressure gauge, and various sensors in a production logging tool positioned near the targeted formation and a surface pressure gauge. 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. The 28 electrodes installed in the ERA string obtained sufficient vertical resolution for heterogeneity identification while the direct-current resistivity measurements enabled deep formation investigations. Therefore, the ERA measurements allowed quantifying the formation heterogeneity and assessing multiphase formation properties on the vertical and lateral scales both comparable to reservoir simulations. A dedicated interpretation tool has been developed, and was fully verified using ERA measurements in well A in the carbonate reservoir. The software integrates three essential components for ERA data analysis: dynamic simulation of fluid and salt transport; electrical simulation of potential distribution and current movements; and parameter inversion using optimization algorithms. The results from applications of this software confirmed the fundamentals of the qualitative interpretation method for ERA data. Furthermore, quantitative estimates of the vertical heterogeneity distributions were obtained that were based on extensive sensitivity simulations and history-matching of simulated resistance and ERA measurements. The key advantage of obtaining the permeability heterogeneity is that the scale of the estimated heterogeneity from ERA measurements is the same as the scale of conventional reservoir simulator blocks. Therefore, there is no need to upscale the permeability distributions obtained from ERA measurements. This may eliminate the uncertainty and unreliability of current upscaling techniques for constructing simulation models. Detailed history matching of the ERA measurements on each electrode was conducted in the study. These results were used to improve the multilayer geological model obtained from open-hole logs and wireline formation tester. In addition to the time-lapse resistivity, the testing system used in this study simultaneously recorded transient pressures, and flow rates during the stepwise water injection and falloff tests. These measurements allowed accurate determination of the artificial transients from pump strokes, friction losses in tubing, and flow rate variations. This enabled to reliably simulate the flow dynamics from reservoir to wellhead using an integrated reservoir and wellbore model. The pressure buildup, water injection, and falloff tests were analyzed to estimate the average effective permeabilities at the connate water and remaining oil saturation conditions. These estimated effective permeabilities should be more representative of the reservoir because they are at reservoir conditions and scale. One distinct feature was that the skin factor changed substantially during the tests. The skin evolution was compounded with pressure loss variation in tubing and varying water injection rates, making reliable analysis challenging. A modified Hall plot, capable of handling a zero flow rate condition in a falloff test between two injection periods, was used to quantify the skin evolution. A numerical simulation model was constructed using a reservoir simulator by integratinga dynamic wellbore model to capture the large friction losses in tubing;the multilayer geological model to represent the detailed formation heterogeneity;the average effective permeabilities from the buildup and falloff tests; andthe substantial skin evolution during the injection periods. The numerical simulation model was matched against the pressure and flow rate histories to verify the data obtained from each individual measurement. It is shown that the technology developed in this study has tremendous potential and unique advantages for reservoir description and management. In particular, by integrating currently available techniques (wireline formation tester, pressure buildup, injection and fall-off tests etc), the ERA test yielded reliable estimates of several key properties, such as vertical permeability heterogeneity, connate water saturation, ROS, movable oil, recovery factor, relative permeability, and capillary pressure, at the scale of simulation grid blocks. The results obtained from this study provide the important properties required for reservoir development and management. These results were delivered in a systematic, integrated, and in situ fashion in this study, whereas any individual method of the existing techniques provided limited results with various constraints. The interpretation and history-matching of ERA measurements as well as detailed pressure history during the injection and fall-off tests provided an integrated environment to verify and fine-tune all the results obtained using each individual technique, which led to unified and consistent formation properties for the reservoir. The integrated methodology allowed a comprehensive characterization of the carbonate reservoir and has the potential to be applied in other fields.
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