Day 3 Wed, November 13, 2019最新文献

{"title":"Geological Facies and Static Rock Types in a Highly Heterogeneous Lower Cretaceous Carbonate Reservoir from an Onshore Field in Abu Dhabi, UAE","authors":"Dario De Benedictis, Shaymaa Ali Al Maskari, Noor Faisal Al Hashmi","doi":"10.2118/197292-ms","DOIUrl":"https://doi.org/10.2118/197292-ms","url":null,"abstract":"\u0000 A Lower Cretaceous reservoir in one of the Abu Dhabi onshore oilfields is the focus of this study aimed 1) to understand, predict and distribute the impact of diagenesis on the reservoir quality, and 2) to define the reservoir Static Rock Types (SRT). This will eventually help to define and predict the reservoir flow units to better frame strategies and choices for reservoir static and dynamic modelling, and to support the decision-making process for the oilfield business plan.\u0000 A fully integrated geological-petrophysical approach was used to carry out the study.\u0000 Nine geological facies are recognized in the reservoir and grouped in four main reservoir facies categories: 1) rudist-bearing facies, 2) grain-supported skeletal and Orbitolinid facies, 3) Bacinella/Lithocodium-coral facies, and 4) mudstone-supported facies. Rudist-bearing and Bacinella/Lithocodium-coral facies represent the best reservoir facies.\u0000 Rudist deposits mainly formed stacked patches- or sheet-like accumulations of reworked skeletal debris on platform top settings in the northeast of the field. In the main reservoir section, geological facies distribution mainly follows the hydrodynamic trend of the depositional settings. Rudist facies properties primarily depend on the depositional texture and the original shell mineralogy and structure (e.g. Caprinids vs. Caprotinids-Requienids).\u0000 Bacinella/Lithocodium-coral deposits form stacked shallowing-up peritidal cycles, representing the genetic units of the lower section of the reservoir. Evidences of epikarst in the uppermost cycles indicate the location of a major sequence boundary correlatable also to neighboring fields.\u0000 The impact of diagenesis appears strongly driven by the depositional facies characteristics, and a paragenetic sequence is proposed for this reservoir.\u0000 A link between geological facies features, including original grain mineralogy and depositional settings, and reservoir quality parameters is established, allowing the prediction and distribution of reservoir properties in the reservoir laterally and stratigraphically.\u0000 Seven SRTs are identified by integrating geological observations and the result of the petrophysical synthesis. SRTs definition closely follows the reservoir stratigraphic framework, allowing creating a two-fold scheme: two SRTs characterize the cyclic peritidal deposits of the Bacinella/Lithocodium-coral section, and five SRTs are identified in the upper rudist-rich section. Petrophysical evidences from MICP data also strongly support this approach.\u0000 A refined geological concept and stratigraphic framework is proposed for the reservoir to integrate the results of the sedimentological/petrographic analysis and petrophysical synthesis.\u0000 Through linking geology and petrophysics, a new robust scheme of SRTs is created to enhance the identification and prediction of the reservoir flow units.","PeriodicalId":11091,"journal":{"name":"Day 3 Wed, November 13, 2019","volume":"41 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86404416","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":"Setting Up of Project Control Learning Academy in ADNOC","authors":"N. Balasubramanian, A. Albreiki, A. Basioni","doi":"10.2118/197639-ms","DOIUrl":"https://doi.org/10.2118/197639-ms","url":null,"abstract":"\u0000 The Project portfolio in the Oil & Gas industry across the value chain is quite large. Significant investments are done in complex environments to manage these Portfolio with annual budgets in International Oil Companies and National Oil Companies running into several billions of dollars. There are many challenges managing Projects and one of the key functions that helps in managing Projects is \"Project Controls\".\u0000 A Unified Value Assurance Process for Projects in the Upstream Business unit was rolled out in July 2015. Based on the learnings from previous project execution and challenges to manage Project schedules, cost, budgets and risks, it was felt that the knowledge level of the Project Management and Project controls function needs to be raised. It was in this context that an idea to set up a Projects Academy came about. Preliminary evaluation for this academy showed extensive efforts, coordination, involvement of external parties and extended time to get the Project Academy set-up. As a quick win, the upstream business line supported the establishment of a \"Project Control Learning Academy\" with in-house resources.\u0000 We will present in this paper how the Project Control Learning Academy was set-up and training being imparted through Human Capital function. We will also address the lessons learnt and the future course of action for enhancing the Academy.","PeriodicalId":11091,"journal":{"name":"Day 3 Wed, November 13, 2019","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86471461","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":"Machine Learning Approach to Classify Water Cut Measurements using DAS Fiber Optic Data","authors":"M. Alkhalaf, F. Hveding, Muhmmad Arsalan","doi":"10.2118/197349-ms","DOIUrl":"https://doi.org/10.2118/197349-ms","url":null,"abstract":"\u0000 A crucial part of optimizing well production is accurate flow metering for both onshore and offshore environments. The industry currently relies on test separators and multiphase meters. These methods have limitations in terms of cost, transportation and safety. In this paper, an alternative method to classify water cut measurement in oil wells based on Distributed Acoustic Sensing (DAS) data and machine learning will be discussed. Fiber optics is an effective tool to perform downhole logging, however, the challenge usually resides in the analysis and processing of the logged data. After performing a flowing survey on an oil well a dataset was developed using the logged DAS data in combination with production logging tool (PLT) measurements. After extraction, processing and labeling the raw DAS data, this dataset is used for training supervised machine learning models.\u0000 In this paper, different classical machine learning models to train this dataset is assessed in terms of accuracy, speed and training/testing segments. The data gathered from the PLT shows a limitation in the variation of water cut percentages between the zones ranging from 71% to 76%. This limits our ability to assess the validity of the model, risk of overfitting, since most points share a similar target value. This is also reflected on the Rayleigh backscatter collected by the laser box where samples from different production zones share a similar value distribution across most frequency ranges. Three different classification machine learning models were selected simple Decision Tree and two ensemble method models—adaptive boost and Random Forest. The ensemble method models offer a parallel and sequential training schemes that increases the variance and reduce the bias in the model. After splitting and shuffling the data, were 10% of the original data was used for training, all models were trained in different percentages of the training set. Multiple metrics were chosen to assess the model's performance including accuracy, F-score and confusion matrices. Random forest classifier appears to be the best choice for this challenge, with a maximum accuracy of 98% and F-score of 0.99. The models show high dependency on low frequencies—lower than 500 Hz—where value distribution across production zones in DAS measurements is comparatively higher. Both ensemble method models are less bias with a maximum feature weight of about 0.1, in contrast, the simple Decision Tree model was highly dependent on a single frequency response. In future work, a more complex and diverse dataset will be collected from wells with a wider range of variances in terms of conditions and types. Moreover, after creating a more robust dataset alternative approaches can be assessed both classical machine learning models—regression and classification—and deep learning.","PeriodicalId":11091,"journal":{"name":"Day 3 Wed, November 13, 2019","volume":"57 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83981291","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":"Application of Machine Learning Tool to Separate Overlapping Fluid Components on NMR T2 Distributions: Case Studies from Laboratory Displacement Experiment and Well Logs","authors":"Pedro A. Romero Rojas, Manuel M. Rincón, P. Netto, Bernardo Coutinho","doi":"10.2118/197684-ms","DOIUrl":"https://doi.org/10.2118/197684-ms","url":null,"abstract":"\u0000 Fluid typing, meaning fluid identification and quantification of each phase, is a significant challenge in NMR data postprocessing, particularly when the fluid spectral distributions overlap in one-dimension (T1, T2 spectra) or two dimensions (T1T2 or DT2 maps). Typical examples are extra-heavy oil and clay-bound water (CBW), heavy oil and capillary-bound water (BVI), free water and light oil or light oil-water and oil-base mud filtrate (OBMF). In these cases, technical limitations in data acquisitions and constraints in the inversion algorithms result in poor spectral resolution for those fluids with very similar physical-chemical properties. This makes very difficult the interpretation of NMR measurements from the laboratory as well downhole.\u0000 We present two case studies: one focused on determining water saturation (Sw) in core samples in a water-oil displacement experiment in the laboratory; the second is about determining the permeability by identifying OBMF from an NMR well log in a medium to light oil-bearing formation. In both cases the targeted fluid component was determined using blind source separation based on independent component analysis (BSS-ICA), which is a machine learning tool capable of separating spectral T2 components (sources) given their statistical independency.\u0000 The results from the displacement experimental show a high correlation (R2 higher than .85) between saturation from the BSS-ICA derived water component and the estimated value from known injected water volumes. In the well log case, the results show that the presence of OBMF and its volume are a good indicator of rock quality of the reservoir layers, as confirmed from several core measurements. Beyond this, the OBMF obtained from BSS-ICA decomposition is used as a key variable in a newly proposed permeability equation. After core calibration the OBMF-based permeability was found to be more representative than the permeability derived from the widely used Timur-Coates equation.","PeriodicalId":11091,"journal":{"name":"Day 3 Wed, November 13, 2019","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78457407","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":"Implementing Talent Management and Its Effect on Employee Engagement and Organizational Performance","authors":"N. Kamel","doi":"10.2118/197665-ms","DOIUrl":"https://doi.org/10.2118/197665-ms","url":null,"abstract":"\u0000 \u0000 \u0000 Over the next decade, attracting and retaining skilled workers will be one of the biggest challenges to oil and gas industry success. Talent management is a business strategy that organizations believe will enable them to retain their top talented employees and improve organization's performance. It is the process of effectively hiring the right talent, preparing them to take up top positions in future, assessing and managing their performance and also preventing them from leaving the organization. The performance of every organization depends on the performance of their employees. If the employees have unique competencies which the competitors cannot replicate, the organization automatically gains a competitive edge over its competitors. So, for managing this unique human capital, the organizations are focusing on creating effective systems and processes for talent management and the approaches to assessing current talent management efforts, identifying gaps and opportunities, and developing integrated action plans that is results-oriented and that can be aligned with each company's unique structure and long term goals. This paper highlights the positive relation between talent management and employee engagement, retention, value addition and improved organizational performance. The study reveals that there is positive association between these variables. This paper also verifies what the recent researchers thought about the positive impacts of talent management. The objectives of the study are to show the impact of Talent Management Techniques in the oil and gas industry on employee's engagement, motivation, loyalty, and performance.\u0000 \u0000 \u0000 \u0000 The present paper has been divided into four sections. In the first part, the changes occurring in the business environment and in particular the challenges faced by the oil and gas industry have been discussed. The second section explores the concept and reviews the available literature on talent management (TM). On the basis of review of literature the factors of talent management were identified and objectives and hypotheses were formulated. In the third section research framework and research methodology finds mention. The fourth section is about results and discussions.\u0000 \u0000 \u0000 \u0000 observations and conclusions are the harvest of different research methods used in the present study e.g. qualitative and quantitative surveys, interviews, workshops and discussion groups. Such methods are aiming at reaching verified and documented evidences of the actual findings derived from studying the impact of talent management on employees' performance and engagement.\u0000 \u0000 \u0000 \u0000 Talent management has become a hot topic everywhere. Review of Literature will explore different definitions, approaches and point of views regarding the Talent Management concepts and techniques. The paper links between findings of literature review and actual results and observations related to current oil and gas companies\u0000","PeriodicalId":11091,"journal":{"name":"Day 3 Wed, November 13, 2019","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81289983","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":"First Wired Drill Pipe Deployment in Adriatic Sea","authors":"A. Salomone, S. Burrafato, G. R. Maccarini, R. Poloni, Valeriano Gioia, A. Concas, G. Tangen, Arve Huse, Lucio Antoniani, Mats Andersen, Sanna Zainoune","doi":"10.2118/197833-ms","DOIUrl":"https://doi.org/10.2118/197833-ms","url":null,"abstract":"\u0000 This paper presents the positive results of the first deployment of wired drill pipe (WDP) technology and along-string measurement (ASM) tools in drilling operations in the Adriatic Sea. The WDP system was used within the frame of a multi-objective testing program, in conjunction with an experimental downhole tool.\u0000 The system allowed transmission of real-time, high-density, low-latency data from logging-while- drilling (LWD) tools and from ASM subs. These tools provided temperature, annular/internal pressure, rotation, and vibration data. This was the first time WDP and ASM tools were used by an operator in the Adriatic Sea. The system was also used for activation and communication with another experimental downhole tool on this project.\u0000 The high-speed telemetry system made it possible to achieve impressive operational and performance benefits. Annular pressure measured along the string provided a better understanding of the drilling mud condition and behavior along the wellbore, thereby allowing the operator to stay in the safe mud-weight window and helping them to avoid unintentional hole fractures or collapse.\u0000 During pumping in and out of hole, swab and surge were also monitored closely with downhole, real- time measurements from the ASM tools. The same effects were controlled after drilling each stand, when the interval drilled was reamed to ensure sufficient hole cleaning.\u0000 While drilling, the system raised the rate of penetration (ROP) limit by removing constraints on data acquisition while still providing the confidence that the hole was being cleaned while drilling. Drillstring vibration was recorded as well, and potential benefit in preventing premature failure of downhole tools were highlighted.\u0000 The test verified that improved drilling performance was enabled using WDP technology. Awareness of downhole conditions and a substantial reduction in risk were also benefits. In addition, the technology unlocked bidrectional communication and control with modern downhole tools.","PeriodicalId":11091,"journal":{"name":"Day 3 Wed, November 13, 2019","volume":"44 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84908876","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":"Exploration and Production: Reducing Geological Risk in the Middle East","authors":"T. Cousins, R. Davies, C. Gravestock, T. Jewell, M. Simmons, O. Sutcliffe","doi":"10.2118/197161-ms","DOIUrl":"https://doi.org/10.2118/197161-ms","url":null,"abstract":"\u0000 Exploration in the Middle East can benefit from the creation of sequence stratigraphy-based, scalable, 3D models of the subsurface that are, in effect, a subsurface digital twin that extends from the plate to pore. Stratigraphic and structural organization are integrated into this model to provide a predictive geological framework for analysis of reservoir- and regional-scale geology. This framework enables testing of novel geologic concepts on the Arabian Plate.\u0000 The first step of model design is to temporally constrain data within a sequence stratigraphic framework. Publically available data were used in the entire construction of this model. This framework enables the generation of plate-wide chronostratigraphic charts and gross depositional environment (GDE) maps that help to define major changes in the regional geological context. The integration of a geodynamic plate model also provides deeper insight into these spatial and temporal changes in geology. The subsurface model also adopts the principles of Earth systems science to provide insight into the nature of paleoclimate and its potential effect on enhancing the predictive capabilities of the subsurface model. A set of plate-scale regional depth frameworks can be constructed. These, when integrated with GDE maps and other stratigraphic data, facilitate basin screening and play risking.\u0000 This plate to play methodology has yielded value through the development of new play concepts and ideas across the Arabian Plate. Exploration has historically relied on the identification of large structures. However, the majority of these are now being exploited. Underexplored stratigraphic traps, and unconventional resources are new concepts that can be better evaluated by using a digital twin of the subsurface. The integration of seismic data and sequence-stratigraphy-calibrated wireline log data can be used to identify the subcrop pattern beneath an unconformity, as well as regions where potential reservoir rocks are in juxtaposition with seals. Intrashelf basins are a key feature of the Arabian Plate. They lead to stratigraphic complexity, yet are key factors for both source rock and reservoir development. From an unconventional perspective, novel, tight plays that exist within or above prominent source rock intervals can also be established.\u0000 Value and insight into previously underexplored play concepts, such as within the Silurian Qusaiba Member and the Cretaceous Shilaif Formation of Abu Dhabi, can thus be generated from the stratigraphic attribution of geoscience data. This data can enable better-informed predictions into \"white space\" away from data control.","PeriodicalId":11091,"journal":{"name":"Day 3 Wed, November 13, 2019","volume":"49 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85693336","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":"Static and Dynamic Characterization of a Tight Reservoir- A Case-Study from Onshore Abu Dhabi Field","authors":"P. Agnihotri, V. Pandey, P. Thakur, M. A. Mansoori, M. Rebelle, Steve Smith, Pranjal Bhatt, G. Zhunussova, S. Hassan","doi":"10.2118/197721-ms","DOIUrl":"https://doi.org/10.2118/197721-ms","url":null,"abstract":"\u0000 Holistic assessment of project economics and subsurface characterization provides a framework to handle challenging reservoirs. Capturing ranked uncertainties based on their impact on the project and meticulous working towards de-risking the project is key for the success of the entire project. Committing increased production from the field is dependent on proper evaluation of the reservoir.\u0000 This paper reviews characterization of a tight reservoir deposited in the intra-shelf Bab basin during lower Aptian time. Initial stage reservoir characterization is critical in formulating reservoir development plan and estimating a realistic assessment of rates and volumes for the field.\u0000 The target formation is a low-permeability (average permeability 0.5 mD) heterogeneous carbonate reservoir sitting directly above and adjacent to a producing carbonate reservoir. It is essential to understand communication between the zones. The pilot well is drilled with 225 ft of conventional core and quad-combo logs. Advanced logs such as resistivity image, cross-dipole acoustic, nuclear magnetic resonance, vertical interference test (VIT), formation pressure (including pressure transient data), and fluid samples were acquired. The main objectives of the evaluation program were to determine the formation pressure, collect representative oil sample(s), conduct vertical interference tests between the sub-zones and collect appropriate data for geomechanical and rock-physics characterization.\u0000 Thorough pre-job planning and cross-discipline cooperation during the operation provided high fidelity log data and interpretation of the data into a coherent result. This included integration of image data with vertical interference tests from the wireline formation tester (WFT) where barriers were confirmed. In addition, NMR permeability was matched and calibrated using pretest mobility measurements and formation pressure data was combined with full waveform advanced acoustic processing to explain the communication between the upper target zone and the lower producing reservoir. Advanced acoustic analysis helped to fully characterize the target formations with stoneley permeability, azimuthal anisotropy, and presence of fractures.\u0000 This paper demonstrates the importance of multi-disciplinary team effort in characterization of challenging reservoirs. It highlights the importance of holistic planning before the execution phase, and keeping a focus on the larger goal while executing individual aspect of a complicated project.\u0000 Formation evaluation measurements have evolved over decades and occasionally it benefits the industry to provide a review of how the latest logging measurements fit together in an integrated manner, for successful evaluation of a challenging reservoir.","PeriodicalId":11091,"journal":{"name":"Day 3 Wed, November 13, 2019","volume":"29 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83338458","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":"Single Point Gas Lift SPGL, A Quick Win Retrofit Gas Lift Application to Maximize Oil Production and Recovery in Greater Bongkot North Field, Thailand","authors":"C. Peerakham, Sineenat Kruennumjai, T. Junmano, Cholavit Boonchun, Krit Ngamkamollert, Pradondate Ut-ang, J. Whangkitjamorn, Suwin Sompopsart","doi":"10.2118/197809-ms","DOIUrl":"https://doi.org/10.2118/197809-ms","url":null,"abstract":"\u0000 In Greater Bongkot North (GBN) Gas Condensate Field located in Gulf of Thailand, many oil wells have recently encountered liquid loading problems. Numerous attempts of gas pressurizing and lowering wellhead pressure have been made but could not sustain continuous oil production. This paper describes the use of innovative technique, Single Point Gas Lift (SPGL) Application, to revive oil production and increase oil recovery from liquid loading wells without the need for an expensive workover operation.\u0000 SPGL is a retrofit retrievable gas lift straddle that can be installed in the existing production tubing via slick-line unit. This fit-for-purpose solution requires 3 main stages of planning and execution. Firstly, design parameters are identified by simulation software e.g. injection depth, injection rate and pressure. Then, gas lift vale (GLV) is installed by punching the tubing at designed depth, followed by installation of gas lift assembly across the punched depth which includes orifice, check valve and pack-off. Lastly, gas supply is injected into annulus and passes through the installed GLV into production tubing.\u0000 The pilot test was conducted at well Bongkot-1, a liquid loaded horizontal oil well. SPGL installation was completed successfully followed by deployment of nitrogen injection unit as gas supply in order to prove the concept of SPGL. The gas lifting operation was begun with well unloading and then varying injection rate to determine an optimum gas injection rate. As a result of total 16 hours of nitrogen injection, the cumulative oil production volume of 3,000 STB was realized, indicating the success of the SPGL application. Consequently, long term production phase by utilizing gas supply from high pressure donor well is being implemented.\u0000 The result proves that SPGL helps to not only revive liquid loading well but also recover more oil reserves and generate more revenues with low cost and simple operation. In 2019, at least 4 oil wells have been scheduled for installation of SPGL application and later with more proven track record of success, it could be extendedly applied to other oil/gas condensate wells, having liquid loading problems, in Greater Bongkot North Field and other fields operated by PTTEP.","PeriodicalId":11091,"journal":{"name":"Day 3 Wed, November 13, 2019","volume":"104 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88516635","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":"Middle East Steamflood Field Optimization Demonstration Project","authors":"E. Behm, Mohammed Al Asimi, Sara Al Maskari, Wladimir Juna, H. Klie, Duc Le, G. Lutidze, R. Rastegar, A. Reynolds, Vinit Tathed, R. Younis, Yuchen Zhang","doi":"10.2118/197751-ms","DOIUrl":"https://doi.org/10.2118/197751-ms","url":null,"abstract":"\u0000 Occidental Mukhaizna completed a steamflood field optimization demonstration project involving about 100 Mukhaizna wells from Mid-December 2018 to Mid-March 2019.\u0000 The field demonstration involves a data analytics process that provides recommendations on the best steam injection allocation among wells in order to improve overall steamflood performance. The process uses a low fidelity physics-based proxy model and cloud-based parallel processing. A field optimization engineer history matches and anchors a proxy model to current well and field operating constraints. The engineer completes hundreds of forward runs as part of an optimization algorithm to identify scenarios most likely to help increase value (oil production per steam injected) over the short term in the field, while honoring all producing and injection well operating ranges. The reservoir management team vets the rate change ideas generated and provides their recommendations for changes so the likely best and most practical overall scenario is implemented. The process is refreshed monthly so field performance results are included immediately, and the optimization process is kept evergreen. The field results so far have been encouraging, yielding an increase in oil production that has exceeded expectations.\u0000 This paper will describe the data analytics field optimization process and workflow, present the baseline performance versus field demonstration results, and share lessons learned.","PeriodicalId":11091,"journal":{"name":"Day 3 Wed, November 13, 2019","volume":"61 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85224819","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}