Authors: Giuseppe Rosi (RGL Reservoir Management) | Da Zhu (RGL Reservoir Management) | Dermot O’Hagan (Suncor Energy)
Inflow Control Devices (ICDs) have been adopted for commercial steam-assisted gravity drainage (SAGD) production for nearly ten years and yet the function they serve is not well understood, and field data evaluating their performance remains scant. Thus, the purpose of the current study is twofold: Firstly, the study derives a simplified analytical model demonstrating how increasing the dP across ICDs acts to improve conformance along a producing lateral. The resulting equation of the analysis acts as a simple rule of thumb for determining an appropriate pressure drop across ICDs to achieve conformance. Secondly, the study evaluates the performance of ICDs that had been installed in four wells, two of which had ICDs installed prior to circulation and two that adopted ICDs later in their lifecycle. The field data shows that ICDs increase production rates and improve conformance along the lateral. These improvements are achieved by an increased drawdown facilitated by the ICDs. This part of the study highlights how early-life results may differ between ICD bearing wells compared to their conventionally completed (slotted liner) offsets: ICD bearing wells exhibit improved conformance and an ability to develop more challenging reservoir resulting in different oil production profiles and composite SORs.
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Authors: Mohammad Soroush (RGL Reservoir Management, University of Alberta) | Morteza Roostaei (RGL Reservoir Management) | Vahidoddin Fattahpour (RGL Reservoir Management) | Mahdi Mahmoudi (RGL Reservoir Management) | Daniel Keough (Precise Downhole Services Ltd) | Li Cheng (University of Alberta) | Kambiz Moez (University of Alberta)
Accurate prediction of flow regime and flow profile in wellbore is among the main interests of production engineers in the quest of optimizing wellbore production and increasing reliability of downhole completion tools especially in SAGD projects. This study introduces a methodology for wellbore monitoring by detecting flow phase and flow regime. In order to develop this method, an advanced multi-phase flow injection experiment was designed and commissioned.
A flow injection setup was developed to test distributed fiber optic sensor installation under different operating conditions, including multi-phase flow (oil, brine and gas), and flow fraction scenarios. Different signal processing methods were applied to extract meaningful features and filter the noise from the raw signals. A statistical analysis was performed to assess the trend of the driven data. Then, typical SAGD models were simulated to assess the results of experimental setup for scale-up purpose and determination of local breakthrough of steam along the well.
Results showed that the Distributed Acoustic Sensing (DAS) data contains different levels of signals for each phase and flow regime. We also found that some level of uncertainties is involved in relating the flow regime and DAS information which could be resolved by improving the sensor installation procedure. In addition, the application of data-driven machine learning methods was found necessary to interpret the signal patterns. Initial results have shown that steam breakthrough along the well can be detected using real time DAS high energy/frequency signals. It can be concluded that including the DAS along with Distributed Temperature Sensing (DTS) is necessary to provide a better picture of steam conformance and SAGD wellbore monitoring. The limitations of the current experimental setup restricted further conclusions regarding the hybrid DAS and DTS application.
This paper is a part of an ongoing project to address the application of the combined DAS and DTS in SAGD projects. The ultimate goal is a downhole monitoring system to oversee the flow phase, flow regime and sand ingress in thermal application. The next phase will address the required improvements for developing a flow loop to handle high temperatures, include sand production and mimic thermal operation conditions.
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Authors: Seyed Abolhassan Hosseini (University of Alberta, RGL Reservoir Management Inc.) | Morteza Roostaei (RGL Reservoir Management Inc.) | Mahdi Mahmoudi (RGL Reservoir Management Inc.) | Ahmad Alkouh (College of Technological Studies) | Vahidoddin Fattahpour (RGL Reservoir Management Inc.)
Production from weakly and unconsolidated sand formations relies on the efficiency of the employed sand control method. Performance of current sand control devices is based on surface size exclusion and depth filtration depending on their geometry and application. In this study, we investigate the possibility of using the advantage of both mechanisms in a single device.
The standard cut point test was used to determine the micron rating of different meshes in order to categorize them in different classes based on the average pore size. Different mesh weaves, namely Dutch twill, reversed Dutch twill and square mesh screens with different micron rating were investigated in terms of filtration performance. In the next step, a dead-end filtration set-up was designed and commissioned to evaluate the flow performance and sand control capabilities of mesh screens. Additionally, a new, customized sand control device was designed and included in the testing matrix to compare its performance with the common mesh screens in the market.
Dead-end filtration results indicated that by choosing the proper combination of morphology, both optimized open to flow area (OFA) and sand control could be achieved. The custom designed hybrid screen performed better compared to other investigated mesh screens with similar micron rating, in terms of both flow and filtration performance. Therefore, the customization was found to be the key parameter to achieve the optimized design. This further emphasizes that by employing the hybrid benefits of surface size exclusion and depth filtration, one can reach the optimized sand control and flow performance. Regarding the weave of different mesh screens, the results did not show any trends that could lead to a conclusion of better performance of a certain weave. Further investigations are required under different testing condition to achieve a conclusive comparison between different mesh types.
This paper investigates the possibility of customized sand control design, which uses the hybrid benefits of surface size exclusion and depth filtration to reach the optimized sand control and flow performance.
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Authors: A. Velayati (University of Alberta) | M. Roostaei (RGL Reservoir Management Inc) | A. Sharbatian (RGL Reservoir Management Inc) | V. Fattahpour (RGL Reservoir Management Inc) | M. Mahmoudi (RGL Reservoir Management Inc) | C. F. Lange (University of Alberta) | A. Nouri (University of Alberta)
Well completion is the process of borehole preparation for the production. Cased and perforated slotted liner completion is used extensively as the completion configuration in the wells drilled into conventional sand formation reservoirs. Such completions may exhibit lower productivity ratios compared to the open-hole condition. The reasons include perforations collapse, flow convergence in the vicinity of the slots and perforations, and the formation damage caused by perforating. These effects have compounding effects as the formation damage magnifies the flow convergence effect and the flow convergence magnifies the skin buildup by the fines migration. In this study, a Computational Fluid Dynamics (CFD) numerical finite volume model was constructed for a vertical cased and perforated completion in a sand reservoir. Results include the skin values that were compared for the different slot and perforation densities. Stability of the perforation tunnels was considered as a variable in this research, and the results were summarized and analyzed in terms of the skin formed as a result of flow convergence. It was found that sanding in perforation tunnels and the resulting change in the permeability of the collapsed tunnel magnifies flow convergence skin significantly, especially in the lower shot densities and this added pressure drop can be very troubling. Results show in lower perforation densities higher pressure drawdowns may trigger sand production due to the tensile failure. Additionally, a parametric study was carried out on the sanding possibilities.
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Authors: J. D. Montero Pallares (University of Alberta) | C. Wang (University of Alberta) | A. Nouri (University of Alberta) | M. Haftani (University of Alberta) | M. Mahmoudi (RGL Reservoir Management) | V. Fattahpour (RGL Reservoir Management)
A three-phase flow large pre-packed Sand Retention Test (SRT) assembly was employed with different screen specifications for typical sand prints within McMurray Formation in Western Canada. Cumulative sand production and retained permeability are utilized as the sand control and plugging performance indicators. Measurements indicate that sand production is highly dependent on the flow dynamics and near-wellbore velocities. Most aperture sizes smaller than two and half times of the mean grain size show a good performance during liquid stages, but wider apertures dramatically failed during steam-breakthrough emulation (three-phase flow). Wire-wrapped screens exhibited an excellent flow performance due to the high open-to-Flow Area (OFA). Existing criteria provide reasonable aperture sizes, especially for finer sands and challenging conditions such as steaminflux. However, the criteria underestimate the slot aperture for coarser sands and conventional liquid production operations. This conservative approach may result in lower productivity performances and diminish the benefits of the high OFA.
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Authors: M. Roostaei (RGL Reservoir Management Inc.) | A. Sharbatian (RGL Reservoir Management Inc.) | V. Fattahpour (RGL Reservoir Management Inc.) | M. Mahmoudi (RGL Reservoir Management Inc.) | A. Velayati (University of Alberta, Edmonton) | A. Ghalambor (Oil Center Research International) | A. Nouri (University of Alberta, Edmonton)
This paper presents an analytical model to calculate the hydraulic fracture initiation pressure from an arbitrarily oriented wellbore in an elastic medium with and without perforations and investigates the competition between axial and transverse fractures. The model predicts the location of fractures and their initiation pressures, in relation to the in-situ stress condition and wellbore azimuth and inclination. Not only has the model been applied to different states of in-situ stress and wellbore orientations, but also the results have been presented in terms of non-dimensional parameters to improve the applicability of the study.
The presence of both transverse and axial hydraulic fractures can cause significant near-wellbore tortuosity. Besides, the stress distribution around the perforation tunnel has a substantial impact on the fracture initiation pressure and thus the fracture geometry near the wellbore. The introduced analytical model was verified against existing models. The model has been successfully applied to different conditions of in-situ stress and wellbore orientations, which were not addressed in previous studies. The results can be used to obtain the optimum well and perforation design in deviated wellbores by providing the minimum fracture initiation pressure and the perforation orientation that minimizes the near-wellbore fracture tortuosity.
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Authors: Izadi, Hossein & Fattahpour, Vahidoddin & Roostaei, Morteza & Mahmoudi, Mahdi & Devere-Bennett, Noel.
Particle size distributions (PSDs) plays an important role in designing sand control screens. Using different techniques (Dry Sieving, LPSA, and Dynamic Image Analysis (DIA)), large number of PSDs could be measured for core samples in a certain project. Moreover, large-scale sand retention tests are becoming common practice in recent years. These tests usually use duplicated sand mixtures of representative PSDs. Therefore, clustering the PSD data is essential for sand control design and sand retention tests. Supervised and unsupervised machine learning algorithms are getting more attention in computational petroleum engineering. Usually there is no clear idea that how many clusters are supposed to be detected in each PSD database. Therefore, due to the limitation for setting the number of clusters, PSD clustering could not be accomplished using conventional clustering algorithms such as k-means or artificial neural networks. As a new approach, PSD clustering based on an incremental clustering algorithm is used here. The proposed algorithm has online incremental learning capability and it is based on adaptive resonance theory (ART). Besides, the number of clusters is not needed to be assigned as an input parameter in the algorithm. The algorithm, based on a self-adaptation approach, tries to minimize the number of clusters. Accordingly, it is appropriate for PSD clustering of big databases. The proposed algorithm can be used in industrial applications such as sand control design and sand control evaluation testing.
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