Numerous wellbore instability problems have been reported when drilling through laminated shale formations because of anisotropic (weak) strength along bedding layers. The anisotropic strength is defined through the analysis of stress distributions around wellbore and angle of intersection (AOI) between well trajectory and weak bedding plane. This paper presents a method to calibrate a wellbore stability model, design mud weight and control breakout width based on analysis of AOI and anisotropic strength. The proposed method includes four (4) steps as follows:AOI is calculated by using bedding plane data (dip angle and dip azimuth) and well trajectory information (well inclination and azimuth).Based on single plane of weakness theory, the stress distributions around deviated wellbores in laminated shales are analyzed to show that failure can occur either along or across bedding planes depending on AOI.The profile of collapse pressure for both isotropic and anisotropic strength model are calculated along with the AOI.Drilling data (mud weight, cuttings/cavings pictures etc.) combined with azimuthal density image are used to choose and calibrate the wellbore stability model. Lab strength test results with different angle to bedding plane are used to calibrate rock strength model and field data are collected and analyzed to define acceptable breakout width. Field data demonstrates that AOI can have a significant effect on wellbore stability. It is observed that severe borehole problems occurred in hole sections with low AOI (<30°) especially when a low mud weight is used to allow a wider breakout. Minor wellbore instability still occurred in some hole sections with low AOI even when the zero breakout criteria was used for mud weight selection. The instability observed can be attributed to swab – decreased ESDs being exerted on the formation while pulling the bottom-hole-assembly out of the hole and time-dependent effect. The ‘zero breakout width’ criterion is recommended for AOI less than 30°, the ‘(90°-Inclination) breakout width’ criterion for AOI between 30° and 60°, and the ‘(90°-2/3*Inclination) breakout width’ criteria for AOI greater than 60°. If the mud weight window permits, then it would be beneficial to increase the mud weight by an extra 0.2 ppg to cover swab effects in shale formations that have an extremely low AOI (<15°). If not, mechanical means to prevent hydrostatic pressure drops such as slower pipe reciprocation or managed pressure drilling (MPD) need consideration.
{"title":"Design Mud Weight and Control Breakout Width Based on Angle of Intersection Analysis","authors":"Jianguo Zhang, Stephen Edwards","doi":"10.2118/210135-ms","DOIUrl":"https://doi.org/10.2118/210135-ms","url":null,"abstract":"\u0000 Numerous wellbore instability problems have been reported when drilling through laminated shale formations because of anisotropic (weak) strength along bedding layers. The anisotropic strength is defined through the analysis of stress distributions around wellbore and angle of intersection (AOI) between well trajectory and weak bedding plane.\u0000 This paper presents a method to calibrate a wellbore stability model, design mud weight and control breakout width based on analysis of AOI and anisotropic strength. The proposed method includes four (4) steps as follows:AOI is calculated by using bedding plane data (dip angle and dip azimuth) and well trajectory information (well inclination and azimuth).Based on single plane of weakness theory, the stress distributions around deviated wellbores in laminated shales are analyzed to show that failure can occur either along or across bedding planes depending on AOI.The profile of collapse pressure for both isotropic and anisotropic strength model are calculated along with the AOI.Drilling data (mud weight, cuttings/cavings pictures etc.) combined with azimuthal density image are used to choose and calibrate the wellbore stability model.\u0000 Lab strength test results with different angle to bedding plane are used to calibrate rock strength model and field data are collected and analyzed to define acceptable breakout width. Field data demonstrates that AOI can have a significant effect on wellbore stability. It is observed that severe borehole problems occurred in hole sections with low AOI (<30°) especially when a low mud weight is used to allow a wider breakout. Minor wellbore instability still occurred in some hole sections with low AOI even when the zero breakout criteria was used for mud weight selection. The instability observed can be attributed to swab – decreased ESDs being exerted on the formation while pulling the bottom-hole-assembly out of the hole and time-dependent effect.\u0000 The ‘zero breakout width’ criterion is recommended for AOI less than 30°, the ‘(90°-Inclination) breakout width’ criterion for AOI between 30° and 60°, and the ‘(90°-2/3*Inclination) breakout width’ criteria for AOI greater than 60°. If the mud weight window permits, then it would be beneficial to increase the mud weight by an extra 0.2 ppg to cover swab effects in shale formations that have an extremely low AOI (<15°). If not, mechanical means to prevent hydrostatic pressure drops such as slower pipe reciprocation or managed pressure drilling (MPD) need consideration.","PeriodicalId":113697,"journal":{"name":"Day 2 Tue, October 04, 2022","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122526205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Aditi Chakrabarti, Mathieu Dauphin, A. Andrews, Lukasz Zielinski, K. Rashid, J. Yuan, A. Speck, Adam Huynh, Justin Power, Vincent Nicolas, Raphael Gadot
Large methane emissions occur from a wide variety of sites with no discernable patterns thus requiring methodologies to frequently monitor for these releases throughout the entire production chain. To cost-effectively monitor widely dispersed well pads, we describe a continuous monitoring system based on the Internet of Things (IoT) to leverage cost-optimized methane concentration sensors permanently deployed at facilities and connected to a cloud-based interpretation platform. Testing at controlled methane release facilities enabled the validation of the sensor performance; fidelity of the atmospheric dispersion modeling underlying our interpretation; and the overall system performance in detecting, localizing, and quantifying methane releases.
{"title":"Rapid Detection of Super-Emitters Utilizing an IoT-Enabled Continuous Methane Emissions Monitoring System","authors":"Aditi Chakrabarti, Mathieu Dauphin, A. Andrews, Lukasz Zielinski, K. Rashid, J. Yuan, A. Speck, Adam Huynh, Justin Power, Vincent Nicolas, Raphael Gadot","doi":"10.2118/210464-ms","DOIUrl":"https://doi.org/10.2118/210464-ms","url":null,"abstract":"\u0000 Large methane emissions occur from a wide variety of sites with no discernable patterns thus requiring methodologies to frequently monitor for these releases throughout the entire production chain. To cost-effectively monitor widely dispersed well pads, we describe a continuous monitoring system based on the Internet of Things (IoT) to leverage cost-optimized methane concentration sensors permanently deployed at facilities and connected to a cloud-based interpretation platform. Testing at controlled methane release facilities enabled the validation of the sensor performance; fidelity of the atmospheric dispersion modeling underlying our interpretation; and the overall system performance in detecting, localizing, and quantifying methane releases.","PeriodicalId":113697,"journal":{"name":"Day 2 Tue, October 04, 2022","volume":"580 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122936046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
K. Strack, C. Barajas-Olalde, Sophia Davydycheva, Yardenia Martínez, P. Soupios
Fluid imaging technologies are used in a wide range of E&P applications. Among geophysical methods, electromagnetics (EM) determines subsurface resistivities and thus responds to fluid changes. On the path to zero carbon footprint, the most significant potential for EM lies in monitoring geothermal, carbon capture, utilization and storage (CCUS), and enhancing oil recovery (EOR). To optimize reservoir fluid monitoring, we calibrate surface measurements to well logs resulting in a 3D anisotropic model consistent with borehole data. This is done before and after depletion or injection to estimate a time-lapse reservoir response. As part of a carbon capture and storage project, we carried out baseline measurements and validated the surface EM data to the 3D anisotropic borehole model. The monitoring workflow for this project can easily be adapted for other applications to support the energy transition. From this, we learned that measurement accuracy requirements higher than 1 % because we are often imaging small anomalies. While there are always limits in acquisition set by industrial noise, we derived two ways of increasing the anomaly. One is by using, similar to a borehole focused logs, focusing methods in the acquisition setup. This is still subject to measurement accuracy limitations and limited to electric fields only. Another way is to add borehole sensors that increase the sensitivity by around a factor of 10. While shallow (around 50 m) is sufficient, they can be extended to deeper borehole sensors, bringing the measurements close to the anomaly and is thus the preferred approach. This, in combination with calibration back to the 3D anisotropic borehole log allows you to certify the data for its information content. This will give you quantifiable ways to derive risk values and significantly reduce acquisition and monitoring operations cost.
{"title":"Surface-to-Borehole Electromagnetics Using an Array System: A Case Study for Co2 Monitoring and the Energy Transition","authors":"K. Strack, C. Barajas-Olalde, Sophia Davydycheva, Yardenia Martínez, P. Soupios","doi":"10.2118/209974-ms","DOIUrl":"https://doi.org/10.2118/209974-ms","url":null,"abstract":"\u0000 Fluid imaging technologies are used in a wide range of E&P applications. Among geophysical methods, electromagnetics (EM) determines subsurface resistivities and thus responds to fluid changes. On the path to zero carbon footprint, the most significant potential for EM lies in monitoring geothermal, carbon capture, utilization and storage (CCUS), and enhancing oil recovery (EOR).\u0000 To optimize reservoir fluid monitoring, we calibrate surface measurements to well logs resulting in a 3D anisotropic model consistent with borehole data. This is done before and after depletion or injection to estimate a time-lapse reservoir response. As part of a carbon capture and storage project, we carried out baseline measurements and validated the surface EM data to the 3D anisotropic borehole model. The monitoring workflow for this project can easily be adapted for other applications to support the energy transition.\u0000 From this, we learned that measurement accuracy requirements higher than 1 % because we are often imaging small anomalies. While there are always limits in acquisition set by industrial noise, we derived two ways of increasing the anomaly. One is by using, similar to a borehole focused logs, focusing methods in the acquisition setup. This is still subject to measurement accuracy limitations and limited to electric fields only. Another way is to add borehole sensors that increase the sensitivity by around a factor of 10. While shallow (around 50 m) is sufficient, they can be extended to deeper borehole sensors, bringing the measurements close to the anomaly and is thus the preferred approach. This, in combination with calibration back to the 3D anisotropic borehole log allows you to certify the data for its information content. This will give you quantifiable ways to derive risk values and significantly reduce acquisition and monitoring operations cost.","PeriodicalId":113697,"journal":{"name":"Day 2 Tue, October 04, 2022","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128344496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ngadiman Helmi Bin, Abidin Szaini Zainal, Shahudin Faizal, Alias Nur Dalila
This technical paper presents the strategy adopted by COMPANY for Remediation of On-Bottom Stability (OBS) Issue during offshore installation of Light Weight Structure (LWS) at Malaysia Water at water depth of 54m. The knowledge sharing is based on the successful remediation work in managing the OBS issue where the substructure experience excessive tilting. The LWS is designed with minimal mudmat. In addition to that, the subsea pin pile is designed to improve substructure on bottom stability issue during substructure installation. However, during actual offshore installation of substructure, the behavior of the substructure upon setting down on seabed was not as per the intended design where the substructure tilting is observed after substructure landing onto pin pile. As mitigation, the following approaches have been implemented to safeguard the substructure from toppling: Safeguard of SubstructureRisk assessment and immediate action have been taken by temporary safe holding the substructure by connecting holdback lines between substructure and installation barge bollards.Revisit OBS engineering study and analysisRevisit on bottom stability engineering study and lifting analysis considering changes to procedure/method by increasing the initial pile length (82m) to allow for early self-penetration.Revisit pile installation and sequenceThe piles have been re-fabricated onboard installation barge by utilizing the chaser rack at DB portside.The chaser rack was fabricated at site with available surplus material onboard DB. Once the revised pile fabrication completed, the piles were installed into the substructure leg for self-penetration.Result of Remediation WorkAfter successfully securing the substructure by installing the 82m pile length at one (1) leg of substructure, it has resulted that the substructure OBS has been improved to allow the COMPANY to proceed with original installation plan sequence as per installation procedure. Ultimately, COMPANY has managed to avoid catastrophic event. Despite all the challenges, the installation of LWS were completed successfully, no damage to property and most importantly with Zero Lost Time Injury (LTI).
{"title":"Remediation of On-Bottom Stability (OBS) Issue During Offshore Installation of Light Weight Structure (LWS) at Malaysia Water","authors":"Ngadiman Helmi Bin, Abidin Szaini Zainal, Shahudin Faizal, Alias Nur Dalila","doi":"10.2118/210197-ms","DOIUrl":"https://doi.org/10.2118/210197-ms","url":null,"abstract":"\u0000 This technical paper presents the strategy adopted by COMPANY for Remediation of On-Bottom Stability (OBS) Issue during offshore installation of Light Weight Structure (LWS) at Malaysia Water at water depth of 54m. The knowledge sharing is based on the successful remediation work in managing the OBS issue where the substructure experience excessive tilting.\u0000 The LWS is designed with minimal mudmat. In addition to that, the subsea pin pile is designed to improve substructure on bottom stability issue during substructure installation. However, during actual offshore installation of substructure, the behavior of the substructure upon setting down on seabed was not as per the intended design where the substructure tilting is observed after substructure landing onto pin pile.\u0000 As mitigation, the following approaches have been implemented to safeguard the substructure from toppling: Safeguard of SubstructureRisk assessment and immediate action have been taken by temporary safe holding the substructure by connecting holdback lines between substructure and installation barge bollards.Revisit OBS engineering study and analysisRevisit on bottom stability engineering study and lifting analysis considering changes to procedure/method by increasing the initial pile length (82m) to allow for early self-penetration.Revisit pile installation and sequenceThe piles have been re-fabricated onboard installation barge by utilizing the chaser rack at DB portside.The chaser rack was fabricated at site with available surplus material onboard DB. Once the revised pile fabrication completed, the piles were installed into the substructure leg for self-penetration.Result of Remediation WorkAfter successfully securing the substructure by installing the 82m pile length at one (1) leg of substructure, it has resulted that the substructure OBS has been improved to allow the COMPANY to proceed with original installation plan sequence as per installation procedure. Ultimately, COMPANY has managed to avoid catastrophic event.\u0000 Despite all the challenges, the installation of LWS were completed successfully, no damage to property and most importantly with Zero Lost Time Injury (LTI).","PeriodicalId":113697,"journal":{"name":"Day 2 Tue, October 04, 2022","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128628944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
D. P. San Roman Alerigi, S. Mutairi, S. Batarseh, Wisam J. Assiri
This work examines the physical principles and effects of high-power laser (HPL) descaling of surface equipment. This contactless technique can fully remove sulfide or calcium carbonate scale without compromising the integrity of the substrate. The method is environmentally friendly, waterless, and energy efficient. It could do away with chemical and mechanical methods for descaling, which have shown low efficiency treating fully-plugged deposits and environmental risks due to chemical use. This paper describes the process through an analysis of its efficiency and impact on the substrate material, the environment, and the implications to production reliability. HPL descaling is described by a multiphysics approach that involves thermal and mechanical processes. The laser causes a phase-change on all or some of the constituents of the scale. This interaction results in spallation, dissociation, and at high energy sublimation. Laser-matter interaction is precise. It produces a small heat affected zone (HAZ) that decays exponentially away from the illuminated area. Thus, the effect of the laser on the surrounding material is minimal to none. Ultrasonic, multi-spectral imaging, microscopy, and statistical analysis are used to analyze the effect of the laser on the substrate material. The environmental impact of the HPL process is compared to existing methods; it is calculated via the carbon intensity of each step and supporting equipment involved in the processes, as well as by its impact to material reuse, waste reduction, and recycling. Scaling can be detrimental to oil and gas production because it may hinder the flow of fluids from and to the well. In surface systems, scale deposits reduce the internal diameter of equipment, thus limiting flow-rate capacity and causing pressure drops across the production network. From a physics perspective, the process is effective because the energy can be delivered with extreme precision on the target. The efficiency of the process depends on the coupling of the HPL with the target and the rate of debris evacuation. The physics are complex but can be optimized through machine learning (e.g. reinforcement learning). The results of the comprehensive characterization demonstrate that HPL descaling preserves the integrity of the substrate. HPL descaling could increase the lifetime of surface equipment affected by scale, and hence contribute to reuse and recycling. The adverse effects of scaling make prevention and removal crucial to the energy industry. Existing methods of scale-removal rely on mechanical or chemical scrubbing, which show varying degrees of success and may deteriorate the substrate. HPL descaling is an environmentally-friendly solution for production reliability; it enables complete descaling and the safe reuse or recycling of scaled equipment.
{"title":"Principles and Advantages of High-Power Lasers for Descaling Surface Equipment","authors":"D. P. San Roman Alerigi, S. Mutairi, S. Batarseh, Wisam J. Assiri","doi":"10.2118/209977-ms","DOIUrl":"https://doi.org/10.2118/209977-ms","url":null,"abstract":"\u0000 This work examines the physical principles and effects of high-power laser (HPL) descaling of surface equipment. This contactless technique can fully remove sulfide or calcium carbonate scale without compromising the integrity of the substrate. The method is environmentally friendly, waterless, and energy efficient. It could do away with chemical and mechanical methods for descaling, which have shown low efficiency treating fully-plugged deposits and environmental risks due to chemical use. This paper describes the process through an analysis of its efficiency and impact on the substrate material, the environment, and the implications to production reliability.\u0000 HPL descaling is described by a multiphysics approach that involves thermal and mechanical processes. The laser causes a phase-change on all or some of the constituents of the scale. This interaction results in spallation, dissociation, and at high energy sublimation. Laser-matter interaction is precise. It produces a small heat affected zone (HAZ) that decays exponentially away from the illuminated area. Thus, the effect of the laser on the surrounding material is minimal to none. Ultrasonic, multi-spectral imaging, microscopy, and statistical analysis are used to analyze the effect of the laser on the substrate material. The environmental impact of the HPL process is compared to existing methods; it is calculated via the carbon intensity of each step and supporting equipment involved in the processes, as well as by its impact to material reuse, waste reduction, and recycling.\u0000 Scaling can be detrimental to oil and gas production because it may hinder the flow of fluids from and to the well. In surface systems, scale deposits reduce the internal diameter of equipment, thus limiting flow-rate capacity and causing pressure drops across the production network. From a physics perspective, the process is effective because the energy can be delivered with extreme precision on the target. The efficiency of the process depends on the coupling of the HPL with the target and the rate of debris evacuation. The physics are complex but can be optimized through machine learning (e.g. reinforcement learning). The results of the comprehensive characterization demonstrate that HPL descaling preserves the integrity of the substrate. HPL descaling could increase the lifetime of surface equipment affected by scale, and hence contribute to reuse and recycling.\u0000 The adverse effects of scaling make prevention and removal crucial to the energy industry. Existing methods of scale-removal rely on mechanical or chemical scrubbing, which show varying degrees of success and may deteriorate the substrate. HPL descaling is an environmentally-friendly solution for production reliability; it enables complete descaling and the safe reuse or recycling of scaled equipment.","PeriodicalId":113697,"journal":{"name":"Day 2 Tue, October 04, 2022","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128658432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper is a continuation of the work presented in URTeC 3718584 (Carlsen & Whitson, 2022), and focuses on practical usage of ‘fractional RTA’ theory when applied to both simulated data and field data from the SPE data repository. Most of the theory presented in Part 1 is kept for completeness. An inherent assumption in most industry RTA is equally spaced fractures. However, as shown in several field studies (Raterman 2017, Gale 2018), the distance between individual fractures tends to be unevenly spaced along the wellbore (e.g., "fracture swarms"). In this paper, we extend the original numerical RTA workflow proposed by Bowie and Ewert (2020) to account for uneven fracture spacing. Acuna's (2016, 2020) heterogeneity parameter, delta (δ), is introduced to generalize the linear flow parameter (LFP) to account for complex fracture systems (LFP’ = Akδϕ1-δ = 4nfhxfkδϕ1-δ). For evenly spaced fractures, δ = 0.5, simplifying LFP’ to the familiar LFP = A√k = 4nfhxf√k. For uneven fracture systems, 0 ≤ δ ≤ 0.5. With known (a) well geometry, (b) fluid initialization (PVT and water saturation), (c) relative permeability relations, and (d) bottomhole pressure (BHP) time variation (above and below saturation pressure), three fundamental relationships exist in terms of LFP' and OOIP. Numerical reservoir simulation is used to define these relationships, providing the foundation for numerical RTA, also wells with complex fracture systems. Namely, that wells: (1) with the same value of LFP', the gas, oil and water surface rates will be identical during infinite-acting (IA) behavior; (2) with the same ratio LFP'/OOIP, producing GOR and water cut behavior will be identical for all times, IA and boundary dominated (BD); and (3) with the same values of LFP' and OOIP, rate performance of gas, oil, and water will be identical for all times, IA and BD. These observations lead to an efficient, semi-automated process to perform rigorous RTA, assisted by a symmetry element numerical model. The numerical RTA workflow proposed by Bowie and Ewert solves the inherent problems associated with complex superposition and multiphase flow effects involving time and spatial changes in pressure, compositions and PVT properties, saturations, and complex phase mobilities. This paper extends the approach to complex fracture systems that can be described by the Acuna parameter δ. Numerical RTA workflow decouples multiphase flow data (PVT, initial saturations and relative permeabilities) from well geometry and petrophysical properties (L, xf, h, nf, φ, k, δ), providing a rigorous yet efficient and semi-automated approach to define production performance for many wells. Contributions include a technical framework to perform numerical RTA for unconventional wells, irrespective of fracture spacing. Semi-analytical models, time, and spatial superposition (convolution), pseudopressure and pseudotime transforms are not required.
{"title":"Numerical RTA Extended to Complex Fracture Systems: Part 2","authors":"Carlsen Mathias Lia, Whitson Curtis Hays","doi":"10.2118/210420-ms","DOIUrl":"https://doi.org/10.2118/210420-ms","url":null,"abstract":"\u0000 This paper is a continuation of the work presented in URTeC 3718584 (Carlsen & Whitson, 2022), and focuses on practical usage of ‘fractional RTA’ theory when applied to both simulated data and field data from the SPE data repository. Most of the theory presented in Part 1 is kept for completeness.\u0000 An inherent assumption in most industry RTA is equally spaced fractures. However, as shown in several field studies (Raterman 2017, Gale 2018), the distance between individual fractures tends to be unevenly spaced along the wellbore (e.g., \"fracture swarms\"). In this paper, we extend the original numerical RTA workflow proposed by Bowie and Ewert (2020) to account for uneven fracture spacing.\u0000 Acuna's (2016, 2020) heterogeneity parameter, delta (δ), is introduced to generalize the linear flow parameter (LFP) to account for complex fracture systems (LFP’ = Akδϕ1-δ = 4nfhxfkδϕ1-δ). For evenly spaced fractures, δ = 0.5, simplifying LFP’ to the familiar LFP = A√k = 4nfhxf√k. For uneven fracture systems, 0 ≤ δ ≤ 0.5.\u0000 With known (a) well geometry, (b) fluid initialization (PVT and water saturation), (c) relative permeability relations, and (d) bottomhole pressure (BHP) time variation (above and below saturation pressure), three fundamental relationships exist in terms of LFP' and OOIP. Numerical reservoir simulation is used to define these relationships, providing the foundation for numerical RTA, also wells with complex fracture systems. Namely, that wells: (1) with the same value of LFP', the gas, oil and water surface rates will be identical during infinite-acting (IA) behavior; (2) with the same ratio LFP'/OOIP, producing GOR and water cut behavior will be identical for all times, IA and boundary dominated (BD); and (3) with the same values of LFP' and OOIP, rate performance of gas, oil, and water will be identical for all times, IA and BD. These observations lead to an efficient, semi-automated process to perform rigorous RTA, assisted by a symmetry element numerical model.\u0000 The numerical RTA workflow proposed by Bowie and Ewert solves the inherent problems associated with complex superposition and multiphase flow effects involving time and spatial changes in pressure, compositions and PVT properties, saturations, and complex phase mobilities. This paper extends the approach to complex fracture systems that can be described by the Acuna parameter δ.\u0000 Numerical RTA workflow decouples multiphase flow data (PVT, initial saturations and relative permeabilities) from well geometry and petrophysical properties (L, xf, h, nf, φ, k, δ), providing a rigorous yet efficient and semi-automated approach to define production performance for many wells. Contributions include a technical framework to perform numerical RTA for unconventional wells, irrespective of fracture spacing. Semi-analytical models, time, and spatial superposition (convolution), pseudopressure and pseudotime transforms are not required.","PeriodicalId":113697,"journal":{"name":"Day 2 Tue, October 04, 2022","volume":"94 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125979376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pipeline corrosion poses significant challenges and risks to the energy industry and its mitigation requires extensive and reliable predictive modeling. Corrosion models based on computational fluid dynamics (CFD) stands as a desirable candidate for its detailed physical characterization and modeling flexibility, but its applications in practical industrial settings is limited by the high computational cost and laborious manual operation in the modeling and sampling process. To address these challenges, we propose a Bayesian active learning method. The method consists of a surrogate model formulated using Gaussian process regression (GPR) to provide rapid model prediction as well as uncertainty quantification, and an adaptive sampling scheme to automate and accelerate the data collection process. Careful dimension reduction guided by both physics and data is also carried out to significantly simplify the sampling space. The capability of the overall method for efficient and automated sampling and surrogate modeling is demonstrated on an example case of corrosion predictive modeling and can be leveraged in industrial applications at a much larger scale.
{"title":"Accelerating Pipeline Corrosion Modeling via Bayesian Active Learning","authors":"Shun Zhang, Ligang Lu, Huihui Yang, Kuochen Tsai, Mohamed Sidahmed","doi":"10.2118/210061-ms","DOIUrl":"https://doi.org/10.2118/210061-ms","url":null,"abstract":"\u0000 Pipeline corrosion poses significant challenges and risks to the energy industry and its mitigation requires extensive and reliable predictive modeling. Corrosion models based on computational fluid dynamics (CFD) stands as a desirable candidate for its detailed physical characterization and modeling flexibility, but its applications in practical industrial settings is limited by the high computational cost and laborious manual operation in the modeling and sampling process. To address these challenges, we propose a Bayesian active learning method. The method consists of a surrogate model formulated using Gaussian process regression (GPR) to provide rapid model prediction as well as uncertainty quantification, and an adaptive sampling scheme to automate and accelerate the data collection process. Careful dimension reduction guided by both physics and data is also carried out to significantly simplify the sampling space. The capability of the overall method for efficient and automated sampling and surrogate modeling is demonstrated on an example case of corrosion predictive modeling and can be leveraged in industrial applications at a much larger scale.","PeriodicalId":113697,"journal":{"name":"Day 2 Tue, October 04, 2022","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127447629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Operators in the unconventional shale oil space are becoming increasingly focused on methods to reduce emissions, mitigate issues due to NGL production, increase sales oil production, and increase safety. Moreover, for facilities to operate unmanned facility designs are required to be simple and robust. Each facility configuration optimizes for a different utility: some allow more flexibility for the economic investment, while others offer familiarity of operation. The option that adds the most flexibility per dollar invested focuses on low-pressure separation with simultaneous heat introduction with minimum necessary storage tanks. Three different facilities are compared utilizing hydrocarbon recovery, NGL production, gas production, compression power, and Reid Vapor Pressure as key metrics. The three layouts include: a heater treater, a vapor recovery tower, and a novel elevated heated separation design that combines the utility of a heater treater and vapor recovery tower. The novel low-pressure stabilization system allows for stabilized oil to be pumped either to storage tanks or directly to the custody transfer point. Emissions stemming from tank vapor and tank vapor management systems are avoided as the oil is stabilized before entering the storage tanks or being transported directly to custody transfer. The novel system can be scaled for higher production rates seen at central processing facilities where traditional equipment such as heater treaters would require operating several parallel production trains. The novel design avoids known operational safety and maintenance issues regarding direct fired heaters and tanks; thus, improving safety and operational cost. Existing facilities designs include equipment such as direct fired heater treaters, inline heat exchangers, vapor recovery towers and tanks. The results from all process simulations and operational data is summarized in an overview comparing the performance of the various facility designs.
{"title":"What's the Best Way to Stabilize Oil in the Permian? An Examination of Different Facilities Layouts","authors":"I. Chan, S. Baaren, Anthony Sarcletti","doi":"10.2118/210446-ms","DOIUrl":"https://doi.org/10.2118/210446-ms","url":null,"abstract":"\u0000 Operators in the unconventional shale oil space are becoming increasingly focused on methods to reduce emissions, mitigate issues due to NGL production, increase sales oil production, and increase safety. Moreover, for facilities to operate unmanned facility designs are required to be simple and robust.\u0000 Each facility configuration optimizes for a different utility: some allow more flexibility for the economic investment, while others offer familiarity of operation. The option that adds the most flexibility per dollar invested focuses on low-pressure separation with simultaneous heat introduction with minimum necessary storage tanks.\u0000 Three different facilities are compared utilizing hydrocarbon recovery, NGL production, gas production, compression power, and Reid Vapor Pressure as key metrics. The three layouts include: a heater treater, a vapor recovery tower, and a novel elevated heated separation design that combines the utility of a heater treater and vapor recovery tower.\u0000 The novel low-pressure stabilization system allows for stabilized oil to be pumped either to storage tanks or directly to the custody transfer point. Emissions stemming from tank vapor and tank vapor management systems are avoided as the oil is stabilized before entering the storage tanks or being transported directly to custody transfer.\u0000 The novel system can be scaled for higher production rates seen at central processing facilities where traditional equipment such as heater treaters would require operating several parallel production trains. The novel design avoids known operational safety and maintenance issues regarding direct fired heaters and tanks; thus, improving safety and operational cost.\u0000 Existing facilities designs include equipment such as direct fired heater treaters, inline heat exchangers, vapor recovery towers and tanks. The results from all process simulations and operational data is summarized in an overview comparing the performance of the various facility designs.","PeriodicalId":113697,"journal":{"name":"Day 2 Tue, October 04, 2022","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122117387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rodica Mihai, E. Cayeux, B. Daireaux, L. Carlsen, A. Ambrus, P. Simensen, Morten Welmer, Matthew Jackson
During recent years there has been an increased focus on automating drilling operations and several solutions are in daily use. We describe here results and lessons learned from testing on a full-scale test rig, the next step in drilling automation, namely autonomous drilling. By autonomous drilling we mean a system capable of taking its own decisions by evaluating the current conditions and adapting to them while considering multiple horizon strategies to fulfill the drilling operation goal. Autonomous drilling was demonstrated during a series of experiments at a full-scale test rig in Norway. The focus of the experiments was to reach the target depth as quickly and as safely as possible. Since the formation at the test rig is very hard, a previously drilled well was filled with weak cement of variable strengths to allow for fast drilling. As part of the experiments, it was planned to have drilling incidents to test the system capabilities in managing arising issues and recover from them. During the experiments no real-time downhole measurements were available, only surface data. In total 500 meters have been drilled in autonomous mode. The autonomous system is built as a hierarchical control system containing layers of protection for the machines, well and the commands, in addition to recovery procedures, optimization of the rate of penetration and autonomous decision-making. The system continuously evaluates the current situation and by balancing estimated risks and performance, e.g. risk of pack-off versus prognosed time to reach the target depth, decides the best action to perform next. The autonomous decision-making system is tightly connected with the control of the drilling machines and therefore it executes the necessary commands to follow up the computed decision. Drilling incidents may occur at any time and an autonomous system needs to be able to adapt to the current situation, such that it can manage drilling incidents by itself and recover from them, when possible. During the experiments, several drilling incidents occurred, and the system reacted as expected. Surface data, together with internally computed data from the autonomous decision-making algorithms, were logged during the experiments. Memory-based downhole data was available after the experiments were concluded. Based on all the data collected, an analysis of the behavior of the system was performed after the experiments. During the drilling experiments at the full-scale rig, the autonomous system adapted its decisions to the surrounding environment and tackled both smooth drilling situations and drilling incidents. To cope with possible lower situational awareness, the autonomous system manages by itself transitions from autonomous to manual mode if necessary. This feature, together with fault detection and isolation capabilities, are crucial for safe operation of an autonomous system.
{"title":"Demonstration of Autonomous Drilling on a Full-Scale Test Rig","authors":"Rodica Mihai, E. Cayeux, B. Daireaux, L. Carlsen, A. Ambrus, P. Simensen, Morten Welmer, Matthew Jackson","doi":"10.2118/210229-ms","DOIUrl":"https://doi.org/10.2118/210229-ms","url":null,"abstract":"\u0000 During recent years there has been an increased focus on automating drilling operations and several solutions are in daily use. We describe here results and lessons learned from testing on a full-scale test rig, the next step in drilling automation, namely autonomous drilling. By autonomous drilling we mean a system capable of taking its own decisions by evaluating the current conditions and adapting to them while considering multiple horizon strategies to fulfill the drilling operation goal.\u0000 Autonomous drilling was demonstrated during a series of experiments at a full-scale test rig in Norway. The focus of the experiments was to reach the target depth as quickly and as safely as possible. Since the formation at the test rig is very hard, a previously drilled well was filled with weak cement of variable strengths to allow for fast drilling. As part of the experiments, it was planned to have drilling incidents to test the system capabilities in managing arising issues and recover from them. During the experiments no real-time downhole measurements were available, only surface data.\u0000 In total 500 meters have been drilled in autonomous mode. The autonomous system is built as a hierarchical control system containing layers of protection for the machines, well and the commands, in addition to recovery procedures, optimization of the rate of penetration and autonomous decision-making. The system continuously evaluates the current situation and by balancing estimated risks and performance, e.g. risk of pack-off versus prognosed time to reach the target depth, decides the best action to perform next. The autonomous decision-making system is tightly connected with the control of the drilling machines and therefore it executes the necessary commands to follow up the computed decision. Drilling incidents may occur at any time and an autonomous system needs to be able to adapt to the current situation, such that it can manage drilling incidents by itself and recover from them, when possible. During the experiments, several drilling incidents occurred, and the system reacted as expected.\u0000 Surface data, together with internally computed data from the autonomous decision-making algorithms, were logged during the experiments. Memory-based downhole data was available after the experiments were concluded. Based on all the data collected, an analysis of the behavior of the system was performed after the experiments.\u0000 During the drilling experiments at the full-scale rig, the autonomous system adapted its decisions to the surrounding environment and tackled both smooth drilling situations and drilling incidents. To cope with possible lower situational awareness, the autonomous system manages by itself transitions from autonomous to manual mode if necessary. This feature, together with fault detection and isolation capabilities, are crucial for safe operation of an autonomous system.","PeriodicalId":113697,"journal":{"name":"Day 2 Tue, October 04, 2022","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122303109","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Carlos Vega-Ortiz, P. Panja, B. McPherson, J. McLennan
Swelling of coal thus reducing permeability is the main detrimental for any carbon dioxide (CO2) capture and storage (CCS) projects. Additionally, CO2 capture from flue gas or direct air is an expensive process. The current commercial simulators are impaired of combining various effects such as fluid segregation, adsorption, Darcy's flow, and permeability change in coal. The objective of this study is to develop a numerical model to simulate flue gas injection in coal. The study is motivated by encouraging preliminary results from lab-scale experiments of injection of flue gas (ideally a mixture of Nitrogen and CO2) in coal. Bench-scale experiments demonstrated the swelling reduction caused by the selective flow of surrogate flue gas N2-CO2 mixture, based on the fluid stratification at sub-critical conditions where the density of pure components in a vertical container causes stratification as predicted from the Grashof number and the thermodynamic properties of fluids. The numerical simulation aims to reproduce and upscale the results from bench-scale Darcy experiments performed in subbituminous coal flowing pure species and mixture of CO2 and N2 at in-situ conditions. A thorough review of the material balance equations coupled with geomechanical stresses and adsorption mechanisms is observed and implemented in a Newton-Raphson model. The stratified fluid in the vertical column is injected in batches onto the coal sample at reservoir conditions producing a cyclic flow of CO2-rich mixture, followed by a N2-rich phase. The repetitive cycles of batch pumping of the stratified CO2-N2 mixture allow the periodic adsorption and desorption interactions, maintaining a high permeability compared to the reduced flow of pure CO2 and the CO2 adsorption in the coal matrix regulated by its partial pressure. Pure CO2 flow in coal resulted in a permeability reduction from 3 to 0.1 mD. The novel optimized CO2-N2 mixture flow ensures an average permeability of 2 mD, while preserving 70% of the maximum CO2 storage capacity. Carbon dioxide storage (CCS) in a suitable geologic setting such as unmineable coal seams are getting research attention for fighting global warming. The model provides important guidelines for the optimization of CO2 capture storage (CCS) in coalbed based on novel strategy of flowing a surrogate flue gas N2-CO2, minimizing the coal swelling due to the adsorption mechanisms, and consequently maintaining a high permeability, while ensuring adsorption and consequently permanent storage of CO2. The proposed methodology offers not only to improve permeability of coal, but also considers the possibility of injecting flue gas mixtures from combustion processes, reducing considerably the cost of surface facilities for CO2 treatment prior to injection. The successful implementation of this technology could potentially solve the problem of global warming at a low-cost process of injection and storage of CO2.
{"title":"Injection of Flue Gas Improves CO2 Permeability and Storage Capacity in Coal: A Promising Technology","authors":"Carlos Vega-Ortiz, P. Panja, B. McPherson, J. McLennan","doi":"10.2118/210419-ms","DOIUrl":"https://doi.org/10.2118/210419-ms","url":null,"abstract":"\u0000 Swelling of coal thus reducing permeability is the main detrimental for any carbon dioxide (CO2) capture and storage (CCS) projects. Additionally, CO2 capture from flue gas or direct air is an expensive process. The current commercial simulators are impaired of combining various effects such as fluid segregation, adsorption, Darcy's flow, and permeability change in coal. The objective of this study is to develop a numerical model to simulate flue gas injection in coal. The study is motivated by encouraging preliminary results from lab-scale experiments of injection of flue gas (ideally a mixture of Nitrogen and CO2) in coal.\u0000 Bench-scale experiments demonstrated the swelling reduction caused by the selective flow of surrogate flue gas N2-CO2 mixture, based on the fluid stratification at sub-critical conditions where the density of pure components in a vertical container causes stratification as predicted from the Grashof number and the thermodynamic properties of fluids. The numerical simulation aims to reproduce and upscale the results from bench-scale Darcy experiments performed in subbituminous coal flowing pure species and mixture of CO2 and N2 at in-situ conditions. A thorough review of the material balance equations coupled with geomechanical stresses and adsorption mechanisms is observed and implemented in a Newton-Raphson model.\u0000 The stratified fluid in the vertical column is injected in batches onto the coal sample at reservoir conditions producing a cyclic flow of CO2-rich mixture, followed by a N2-rich phase. The repetitive cycles of batch pumping of the stratified CO2-N2 mixture allow the periodic adsorption and desorption interactions, maintaining a high permeability compared to the reduced flow of pure CO2 and the CO2 adsorption in the coal matrix regulated by its partial pressure. Pure CO2 flow in coal resulted in a permeability reduction from 3 to 0.1 mD. The novel optimized CO2-N2 mixture flow ensures an average permeability of 2 mD, while preserving 70% of the maximum CO2 storage capacity.\u0000 Carbon dioxide storage (CCS) in a suitable geologic setting such as unmineable coal seams are getting research attention for fighting global warming. The model provides important guidelines for the optimization of CO2 capture storage (CCS) in coalbed based on novel strategy of flowing a surrogate flue gas N2-CO2, minimizing the coal swelling due to the adsorption mechanisms, and consequently maintaining a high permeability, while ensuring adsorption and consequently permanent storage of CO2.\u0000 The proposed methodology offers not only to improve permeability of coal, but also considers the possibility of injecting flue gas mixtures from combustion processes, reducing considerably the cost of surface facilities for CO2 treatment prior to injection. The successful implementation of this technology could potentially solve the problem of global warming at a low-cost process of injection and storage of CO2.","PeriodicalId":113697,"journal":{"name":"Day 2 Tue, October 04, 2022","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129052860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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