Day 2 Tue, November 01, 2022最新文献

{"title":"Predictive Analytical Solution to Permeability in Horizontal Wells from Multi Probe Production Logging and Flowing Gauge Data","authors":"Rathnakar Reddy Peesu, D. Voleti, Nnamdi Dike, Sara Al Ameri","doi":"10.2118/211611-ms","DOIUrl":"https://doi.org/10.2118/211611-ms","url":null,"abstract":"\u0000 Log permeability for reservoir models is generally sourced from core measurements by calibrating to well-test permeability. Conventional approaches are challenged in carbonate reservoirs due to complex depositional and diagenetic alterations. The calibration to well test usually has the basis of pressure buildup (PBU) analysis from limited pilot holes. Horizontal drilling enhanced reservoir recoveries by horizontal drain holes instead of vertical producers. The certainty of a robust permeability model is scrutinized in history matching at the horizontal drain holes. Therefore, it is mandatory to reconcile the log permeability to drawdown permeability in horizontal drain holes by honoring measurement path. The measurement path brings in noticeable effects to permeability in heterogeneous carbonate reservoirs if it is pressure build up or pressure drawdown. The objective of paper is to demonstrate a solution to permeability estimation by sensitizing measurement type, scale, path, and environment in horizontal wells.\u0000 An analytical workflow is developed with field examples by integrating Multi-Probe production logging (PLT) with downhole gauge data while flowing. The prerequisites are to have gauge data for a sustained and stable flow period followed by a long shut in for pressure build up. Thereafter, Multi-Probe production logging was acquired for flowing passes and shut-in passes. In general, pressure transient behavior in horizontal well is mathematically represented by pressure diffusivity equation (Goode & Thambynayagam, 1987) with four possible flow periods. An automated process is programmed in python to detect transient flow regime from gauge data. This denotes the possible flow regime with a characteristic slope which represent the transient conditions during production logging. Multi-Probe PLT data is processed for inflow profile and zonal contributions from velocity and holdup profile conforming to reservoir flow units interpreted in vertical pilot well. Drawdown permeability is estimated from the solutions to pressure diffusivity equation based on estimated downhole fluid rates, identified flow regime and boundary conditions.\u0000 A discrete drawdown permeability from PLT flow profile is estimated as per transient flow regime in horizontal drain holes of a heterogeneous carbonate reservoir. Reconciliation of log permeability with drawdown permeability distinguished prominent flow units in the reservoirs. The results highlighted the critical pitfalls in static to dynamic reconciliation related to reservoir heterogeneity, measurement path, apparent skin variation across flow units and multi-phase effects. The workflow had overcome averaging nature of PBU permeability and the data scarcity in terms of PBU in vertical pilot wells.\u0000 The demonstrated solution involves an automated process to quickly detect flow regime and highlights the integration of prior gauge survey with production logging results. The merit of the solution is to detect baf","PeriodicalId":249690,"journal":{"name":"Day 2 Tue, November 01, 2022","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131773216","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}

{"title":"Reservoir Characterization, Bridging the Scale from Micro to Macro","authors":"Y. Bouzida, E. Cazeneuve, A. Mavromatidis, Khalfan Al Ali, T. Leythaeuser","doi":"10.2118/211693-ms","DOIUrl":"https://doi.org/10.2118/211693-ms","url":null,"abstract":"\u0000 This paper describes the reservoir characterization of a carbonate formation using acoustic and borehole imaging log in a novel way. Interpretation of the interplay between stratigraphic and structural reservoir elements allows additional understanding of the hydrocarbon trapping mechanism and informs decisions on the well testing program and future well placement.\u0000 High-resolution Borehole Images (BHI) have historically been one of the most widespread geological evaluation tools and they continue to be a cornerstone for providing precise data on the facies and fractures intersected by the well. The shallow depth of investigation of wellbore imaging tools can now also be usefully augmented by the acoustic, Dipole shear processing.\u0000 Patented Deep Shear Wave Image (DSWI) methodology allows identification of geological interfaces with a depth of investigation up to 110 feet away from the borehole. The processed data bridges the gap between wellbore images and field scale seismic data and so can guide meaningful reservoir descriptions and fracture characterization at the geo-cellular mode scale.\u0000 Combination of the two separate imaging measurements compensates for the limitation of each logging tool's capabilities and helps increase the range of feature detection from near borehole to as much as 110 or more feet away from the well. The statistically rich borehole imaging data can be used to help confirm the detailed characteristic of these features and how the facies/lithology affect the fracture properties. BHI also calibrate the DSWI features true azimuth, while the DSWI data can help confirm fracture hierarchies and fracture bed interaction away from the borehole.\u0000 The current study highlighted that the different scales of measurement allow additional quantified analysis of the fracture hierarchy and leads to proposal of conceptual fracture models that recognize bed-bound and non-bed-bound fractures sets. The reservoir itself is highly stratified with intercalations of limestone, mudstone and evaporite. Hydrocarbon (HC) presence, defined by an acoustic derived HC Index (but validated with conventional resistivity logging), suggests that oil is preferentially trapped in successive porous layers, but enhanced in some intervals by the additional presence of fractures. The Reservoir pressure points have indicated that only main faults-oriented NNW-SSE could potentially compartmentalized the reservoir. Additional wells and data integration are needed to confirm it.\u0000 The DSWI is also useful to calibrate the poor to moderate seismic data in this field by detecting sub-seismic features that have an impact on the reservoir and helps in updating the geological and reservoir model.","PeriodicalId":249690,"journal":{"name":"Day 2 Tue, November 01, 2022","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127884636","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}

{"title":"Applied Framework for Managing Sustainable Retrograde Gas Condensate Reservoirs","authors":"Rowa Tawfiq, Asma Alahmadi","doi":"10.2118/211341-ms","DOIUrl":"https://doi.org/10.2118/211341-ms","url":null,"abstract":"\u0000 Managing retrograde gas condensate reservoirs comes with its set of challenges. To maximize recovery and ensure the sustainability of reservoirs, the reservoir engineer must ensure the proper well placement, choose the best completion, and perform regular reservoir surveillance. This paper discusses an applied framework for managing retrograde gas condensate reservoirs, to ensure the longevity of the reservoir and maximize performance.\u0000 The process of managing sustainable retrograde gas condensate reservoirs entails proper well placement, which can be achieved through an in-depth assessment of the targeted geological formation in terms of reservoir development. This is further assessed through acoustic impedance maps, seismic data, and any reservoir modeling available. Also, choosing the correct completion of the well is a function of the information obtained from well logging and sampling. Finally, proper reservoir surveillance should be implemented after the well is put on production. Information such as pressure and temperature data, zonal production contributions, and pressure build-up tests should be obtained regularly.\u0000 Following proper well placement, correct completion choice, and regular reservoir surveillance can aid in maximizing production and ensure the sustainability and longevity of the reservoir. Utilizing a comprehensive geological model to study both the structure and development of the reservoir can aid in choosing the optimum well type: vertical, horizontal, or deviated, as well as the required completion. Once well logging and sampling are performed, an optimal completion method can be deployed. Typically, porous sandstone reservoirs require some sort of sanding control method to not impede the production of gas. Tight gas reservoirs would require fracking to increase permeability, and sand control to reduce sand production. As an alternative, tightness can also be overcome by drilling horizontal wells with high inclination to increase reservoir contact. Finally, reservoir surveillance is of utmost importance for retrograde gas condensate reservoirs. Reservoir fluid characterization aids in determining the dew point pressure, after which condensate starts to produce. Several methods are discussed to reduce the effect of condensate production.\u0000 This paper discusses a framework for managing a retrograde gas condensate reservoir, where successful planning, completion, and surveillance can be applied. The article also sets forth a flow chart to exemplify the optimum path to manage and sustain retrograde gas condensate reservoirs successfully.","PeriodicalId":249690,"journal":{"name":"Day 2 Tue, November 01, 2022","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128718273","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}

{"title":"How to Build a Digital Twin with Strong Justification & Return of Investment: Case Study from OQ Oman","authors":"Khulood Mohammed Al Maawali, Khalid Khamis Al Fahdi","doi":"10.2118/210991-ms","DOIUrl":"https://doi.org/10.2118/210991-ms","url":null,"abstract":"\u0000 OQ recognizes the significancy of new technologies driving all industries, and in these days alongside with the latest generation of information technologies, including artificial intelligence, machine learning, cloud computing, internet of things and big data, The roles of virtual space are becoming more of a value and the links between the physical and virtual worlds are more intense than ever before. Introducing such development of virtual spaces is allowing for more technologies, and it is well considered an enabler for a proper digital transformation. OQ is an integrated energy company working on oil & gas, where asset reliability and availability are a key aspect to be monitored and maintained. At OQ we admit the fact that this revolution of technology -if implemented in the right way- could result in enhancing the operation, reducing maintenance costs, and increasing profits. This was the driver of the study, which started by reviewing the readiness and needs across OQ brown assets and ended up with a design of Digital Twin (DT) technology with the highest return of investment and strong justification.\u0000 The case study summarized the procedure for building a digital twin for OQ brown fields, initiated by assisting OQ assets, highlighting the areas of impact, building strong use cases, selecting the most critical for a pilot project, and designing the project rollout. The procedure was built based on internal and external involvements, internally with different stakeholders inside OQ, and externally with some of the top technology providers of digital twin globally, which allows for proper alignment and for discovering the most recent available solutions and related technologies in the scope of the project. This case study has its value as it is contributing in guiding similar industries in designing their own deployment plan of digital twin considering digital twin strategies to support the consistent and systematic rollout of the technology.","PeriodicalId":249690,"journal":{"name":"Day 2 Tue, November 01, 2022","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129121901","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}

{"title":"Deep-Learning-Based Surrogate Reservoir Model for History-Matching Optimization","authors":"Alaa Maarouf, S. Tahir, Shi Su, Samat Ramatullayev, Coriolan Rat, Chakib Kada Kloucha, Hussein Mustapha","doi":"10.2118/211061-ms","DOIUrl":"https://doi.org/10.2118/211061-ms","url":null,"abstract":"\u0000 Achieving a high-quality history match is critical to understand reservoir uncertainties and perform reliable field-development planning. Classical approaches require large uncertainty studies to be conducted with reservoir-simulation models, and optimization techniques would be applied to reach a configuration where a minimum error is achieved for the history match. Such techniques are computationally heavy, because all reservoir simulations are run in both uncertainty studies and optimization processes.\u0000 To reduce the computing requirements during the optimization process, we propose to create a robust deep-learning model based on the hidden relationships between the uncertainty parameters and the reservoir-simulation results that can operate as a surrogate model for computationally intensive reservoir-simulation models.\u0000 In this paper, we present a workflow that combines a deep-learning, machine-learning (ML) model with an optimizer to automate the history-matching process. Initially, the reservoir simulator is run to generate an ensemble of realizations to provide a comprehensive set of data relating the history-matching uncertainty parameters and the associated reservoir-simulation results. This data is used to train a deep-learning model to predict reservoir-simulation results for all wells and relevant properties for history matching from a set of the selected history-matching uncertainty parameters. This deep-learning model is used as a proxy to replace the reservoir-simulation model and to reduce the computational overhead caused by running the reservoir simulator. The optimization solution embeds the trained ML model and aims to deliver a set of uncertainty parameters that minimizes the mismatch between simulation results and historical data. At each optimization iteration, the ML model is used to predict the well-level reservoir-simulation results.\u0000 At the end of the optimization process, the optimal parameters suggested by the optimizer are then validated by running the reservoir simulator.\u0000 The proposed work achieves high-quality results by leveraging advanced artificial-intelligence techniques, thus automating and significantly accelerating the history-matching process.\u0000 The use of uncertainty parameters as input to the deep-learning model, and the model's ability to predict production/injection/pressure profiles for all wells is a unique methodology. Furthermore, the combination of the deep-learning surrogate reservoir model with optimization methods to resolve history-matching problems is advancing the industry's practices on the subject.","PeriodicalId":249690,"journal":{"name":"Day 2 Tue, November 01, 2022","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116745672","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}

{"title":"Successful Intervention into a Six-Leg Multi-Lateral Well Using an Electrical MultiLateral Tool Deployed on Real-Time Hybrid Coiled Tubing for Acid Stimulation of a Kuwait Field - A Case Study","authors":"F. Bastaki, Mohammed Al Matar, Mizan Omar, Jassim Barki, M. Jamal, Fayez Al-Mutairi, S. El-Aziz, Zakaria Albahar, Mehanna Al-Mehena, Nakul Khandelwal, Sapna Chawla, Rishi Gaur, Mohammad Alkreebani, Joshua Travesso","doi":"10.2118/211346-ms","DOIUrl":"https://doi.org/10.2118/211346-ms","url":null,"abstract":"Multilateral technology offers multiple benefits to oil and gas operators, including lowering the field development cost by minimizing wellsite construction work and increasing reservoir contact leading to enhanced reservoir production. To gain full advantage of these complex wells, they must be stimulated properly. The operator in Kuwait drilled, cased, and cemented a six-leg, level IV multilateral well targeting two different formations, the upper and lower Tuba. This provided various production options and the flexibility of taking production from either the lower or upper laterals or even all six laterals to help mitigate the risks of drilling horizontal or directional wells. As such, multilateral technology can positively transform the economic viability of reserves in marginal fields. Exploiting the advantages of multilateral technology requires a multi-disciplinary approach to select appropriate well structure, completion design, re-entry flexibility, and production longevity. Intervention in this level IV multilateral well presented several challenges, such as Oil Based Mud (OBM) in all the laterals, encountering a fault in one of the laterals while drilling, and high shale content that can lead to stuck Coiled Tubing (CT) and the loss of fluid returns. Real-time hybrid cable CT was chosen along with an electric multilateral tool to mitigate the various risks involved. This solution includes a hybrid fiber optic and electrical cable installed in the CT string and a modular Bottom Hole Assembly (BHA) equipped with various sensors. An electrically controlled indexing tool, inclination sensor, tool- face sensor, downhole camera, hydraulic knuckle joint, and pulsating stimulation tool were used as part of the BHA to enable real-time diagnostics and dynamic controls from the surface to successfully enter and stimulate all the lateral legs. This configuration helped identify each different lateral without the need to tag the bottom of each lateral. The paper focuses on applications, strategies, and benefits of specific tool configurations developed for multilateral well intervention, enabling the stimulation of all the lower Tuba laterals. This was a particularly challenging operation due to shale in one of the laterals causing several instances of stuck CT with the possibility of a collapsed hole mitigated by using the real-time camera in the BHA. This paper includes strategies that address proper tool selection, confirmation of lateral entry, hydrostatic pressure balance, borehole stability, and acid design. It also explores the potential of new, synergistic strategies and work processes planned for stimulation of the upper Tuba field.","PeriodicalId":249690,"journal":{"name":"Day 2 Tue, November 01, 2022","volume":"192 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115484620","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}

{"title":"South Oman Cluster GHG and Carbon Footprint Reduction Journey - Achievements and Aspirations","authors":"M. Muthalaly, K. Kumar, Pankaj Agarwal, R. Mihajlov, Zeyana Kindi, Fatma Harthy, Aiman Quraini, A. Hadhrami","doi":"10.2118/210952-ms","DOIUrl":"https://doi.org/10.2118/210952-ms","url":null,"abstract":"\u0000 South Oman Sour Cluster facilities have historically recorded peak total Green House Gas Emission (GHGE) of ~2.1 million tons CO2e in 2019 representing largest volumes within Petroleum Development Oman (PDO). The key contributing factors were lower system availability which resulted in large non-routine flaring and Miscible Gas Injection (MGI) process which requires high power consumption. This paper describes an effective integrated approach undertaken through flaring reduction initiatives, operational excellence and new technology deployments to reduce GHGE footprint within the company/Oman. These initiatives contribute towards a greener hydrocarbon industry and helps in combating climate change.\u0000 Non-routine Flaring has been reduced through initiatives to improve system availability (upgrade of control and safeguarding systems, critical parts), focused maintenance campaigns and inline well testing. Critical compressors are being spared where economical and upcoming projects are adopting parallel configurations. Flare Gas Recovery solutions are being deployed with help of new technologies (gas sweetening and flue gas cleaning) to recover all safety flaring and partial non-routine flaring volumes. Local Fuel gas consumption is being phased out. Power grids are being sourced from renewable sources and power plants are being shifted to hydrogen where possible and deployment of CCUS technologies.\u0000 As a result of the ongoing initiatives, South Oman Cluster facilities recently in 2021 achieved ~50% reduction in flaring volumes and overall ~25% drop in GHGE compared to 2019 levels. In line with the decarbonization roadmap, total GHGE is predicted to further reduce and reach ~0.7 million tons CO2e (67% lower) by 2030 and ~0.3 million tons CO2e (85% lower) by 2044. These radical impacts were a result of an integrated approach to GHGE issues by identifying all possible sources of emissions, mitigating them as much as possible and addressing the rest through various pragmatic solutions despite the challenges of being critical sour facilities. A core GHGE task force was put in place to continuously evaluate performance, scout for feasible initiatives and pursue its execution to realize its gains. South Oman Sour Cluster GHGE journey, learnings and approach could be replicated elsewhere in the Hydrocarbon industry thereby contributing to a Green Planet.","PeriodicalId":249690,"journal":{"name":"Day 2 Tue, November 01, 2022","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115704090","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}

{"title":"Halite Pore Space Plugging Evaluation Based on the Logging Data for the Cambrian Ara Group Intra-Salt Tight Carbonate Reservoirs (South Oman Salt Basin)","authors":"Dmitrii Smirnov, M. Hashmi, A. Al Hadhrami, Omar Mohammed Al Isaee, Khayrutdinov Fanis, P. Agrawal, K. Kumar, Saqer Kaabi","doi":"10.2118/211652-ms","DOIUrl":"https://doi.org/10.2118/211652-ms","url":null,"abstract":"\u0000 There has been a string of exploration discoveries in Cambrian Ara Group intra-salt carbonate reservoirs in the South Oman. Some of the reservoirs failed to produce at expected rates due to halite presence in the pore space, which is one of the highest risks for hydrocarbon exploration in this area. The objective of this study was to define novel quantitative algorithm to estimate halite volumes in the pore space.\u0000 Although halite cementation is known as a major risk for hydrocarbon production, a limited number of studies have focused on the impact of halite cementation on productivity, well integrity and ultimate recovery. The quantitative halite volume evaluation based on the logging data required an integrated approach to open hole and cased hole data collection and analysis. The open hole data included: thin section and XRD core analysis, density, neutron, sonic, resistivity, formation pressure and sigma capture-cross section. Net pay cut-off based on calculated halite volume was defined. Cased hole production logging was used to confirm net cut-off definition. The integrated logging data analysis and the developed quantitative halite volume evaluation algorithm mainly based on sigma log was successfully implemented in a few ongoing development projects. The evaluation results were successfully used for hydrocarbon volume calculations, well placement and perforation interval selection to improve production performance and reduce field development uncertainty in recoverable volumes. Understanding of consistent pattern for halite distribution allow improve exploration success. Avoiding perforation of intervals with high halite content in the pore space reduced production deferment due to surface equipment and tubing plugging by salt. Appreciation for the role of halite plugging in the reservoirs properties distribution and deterioration significantly improve history match for hydrodynamic models. The evaluation algorithm for quantitative halite volume estimation in the pore space have been developed and introduced for the first time and benefits from its implementation are expected for the upcoming exploration and development projects for the salt encased carbonate reservoirs.","PeriodicalId":249690,"journal":{"name":"Day 2 Tue, November 01, 2022","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114182378","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}

{"title":"Unlocking Oil Reserves from Inaccessible Platforms Utilising DSL (First Implementation in Egypt)","authors":"M. Koriesh, M. Elwan, E. Shahin, A. Basyouni, Hamdy Soliman, O. Okasha, Mohamed Saleh, F. Heaney","doi":"10.2118/211227-ms","DOIUrl":"https://doi.org/10.2118/211227-ms","url":null,"abstract":"\u0000 Offshore Oil accounts for 30% of the world's liquid hydrocarbon production. As offshore platforms age, as is the case with some of the production facilities in the Gulf of Suez, these structures will have a increased load restriction, which makes it difficult to perform simple interventions, and forces the operator to deploy a Jackup rig or do a barge assisted operation. Some identified opportunities are not performed due to the high cost and the inherent subsurface uncertainty with brownfield assets. An alternative solution is a new generation intervention tool that allows signal transmission on conventional slickline wire.\u0000 Real-time slickline (DSL) perforations use a unique technology to allow signal transmission on a standard slickline. The technology uses downhole battery-powered telemetry embedded in the downhole tool string. A radio-frequency (RF) antenna installed below the stuffing box is responsible for sending & receiving RF signals through the wire. The wire is coated with a proprietary engineered coating to ensure quality signal transmission and protects against corrosive wellbore fluids. The technology allows real-time depth correlation, pressure, temperature & vibration measurements while perforating. Moreover, the technology offers on-command explosive triggering, which improves safety over the older memory/timer version.\u0000 Real-time slickline perforating was successfully introduced in the Gulf of Suez, accessing two platforms with structure load weight limitations that could not accept a conventional e-line unit. The optimized weight of digital slickline equipment was only 8 tons, compared to 35 Tons for e-line. Two wells were successfully perforated on two different platforms, adding 1200 BOPD at 10% of the rig-assisted intervention cost. The real-time slickline deployment enhanced the intervention efficiency and saved $950,000 in operating expenses.\u0000 In addition to the successful deployment of several perforation runs without operational problems, the additional capabilities of DSL for surface readout (SRO) pressure & temperature data allowed the operator to optimize the time on the platform and maximize efficiency. The ability to add feedthrough jars to the string helped complete one job when the tool BHA struggled to get into the tubing after perforation. This capability is not available in conventional E-line.\u0000 Real-time slickline (DSL) operations are the next generation for rigless interventions providing access to wells that e-line could not cost-effectively intervene and complete this task at a much lower cost.","PeriodicalId":249690,"journal":{"name":"Day 2 Tue, November 01, 2022","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115765790","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}

{"title":"Integrated Rig Management Platform","authors":"Flavio Ferrari, D. Fenaroli, J. Michelez, Jacopo Magni","doi":"10.2118/211767-ms","DOIUrl":"https://doi.org/10.2118/211767-ms","url":null,"abstract":"\u0000 Objectives/Scope: The Integrated Rig Management System provides the implementation of a comprehensive digital platform to manage, analyse and display drilling data coming from different sources (rig sensors, reporting, equipment description, engines data, …). This integration fulfils several objectives such as empowering analytics, automatizing reporting, supporting operations performance, and rig management. Methods, Procedures, Process: The system is made of 5 modules, of which 2 directly operated on the rig: and 2 collecting data from all rigs: A Reporting module that gathers a full set of daily reports such as DDR, HSE report and BHA assembly,… This module also provides a connection between the planned and realized activities, in order to support maintenance and logistics. A Multi-Wells/Rigs Performance module that displays benchmark analyses from all rigs, by type of operation, and equipment, giving a statistical indication on the technical limit to reduce invisible lost time or greenhouse gases emissions. A Real-Time Operations Monitoring module that supports ongoing activities with powerful analyses and insightful performance KPIs. This module also supports the Reporting through the recognition of main rig states by analysing rig sensor data. A Predictive module that uses a predictive algorithm to anticipate and avoid wellbore issues with a machine learning approach.• A Data Manager module that aggregates and processes the data coming from the drilling rigs, combining it with daily drilling reporting. Results, Observations, Conclusions: The values generated by this Integrated Rig Management System are supporting all main corporate objectives in terms of operations, logistics and carbon footprint. Regarding the operations, the system provides impartial and detailed KPIs on operation performances, in order to calculate the Invisible Lost Time to be eliminated in future operations. The system has demonstrated up to 8% time and cost reduction on entire well campaigns. For the logistics, the system crosses the near future activities with any rig resources (equipment, services, personnel, ⋯). Through specific APIs the system makes information available to third parties solutions for maintenance, logistics ad personnel management. A considerable amount of time is saved by the integration of operational and organizational systems. Finally, considering the carbon footprint, the system provides analyses on how much each operation consumes in terms of energy and makes recommendations on how many diesel engines must be kept running in each situation to minimize the related GHG emissions. Novel/Additive Information: The main innovation is the integration of different objectives into one single platform. Reporting data and rig sensor data are obviously creating a great value to operations, but less commonly they also create value for maintenance, logistics, and GHG reduction. The system is in a continuous stream of upgrades, in order to integrate grad","PeriodicalId":249690,"journal":{"name":"Day 2 Tue, November 01, 2022","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126211231","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}