Intelligent Waterflood Optimization Advisory System – A Step Change Towards Digital Transformation

2021 ◽  
Author(s):  
Samat Ramatullayev ◽  
Muzahidin Muhamed Salim ◽  
Muhammad Ibrahim ◽  
Hussein Mustapha ◽  
Obeida El Jundi ◽  
...  

Abstract In this paper, we discuss the development of an end-to-end waterflood optimization solution that provides monitoring and surveillance dashboards with artificial intelligence (AI) and machine learning (ML) components to generate and assess insights into waterflood operational efficiency in an automated manner. The solution allows for fast screening of waterflood performance at diverse levels (reservoir, sector, pattern, well) enabling prompt identification of opportunities for immediate uptake into an opportunity management process and for evaluation in AI-driven production forecast solution and/or a reservoir simulator. The process starts with the integration of a wide range of production and reservoir engineering data types from multiple sources. Following this, a series of monitoring and surveillance dashboards of key units and elements of the entire waterflood operations are created. The workflows in these dashboards are framed with key waterflood reservoir and production engineering concepts in mind. The optimization opportunity insights are then extracted using automated traditional and AI/ML algorithms. The identified opportunities are consolidated in an optimization action list. This list is passed to an AI-driven production forecast solution and/or a reservoir simulator to assess the impact of each scenario. The system is designed to improve the business-time decision-making cycle, resulting in increased operational performance and lower waterflood operating costs by consolidating end-to-end optimization workflows in one platform. It incorporates both surface and subsurface aspects of the waterflood and provides a comprehensive understanding of waterflood operations from top-down field, reservoir, sector, pattern and well levels. Its AI/ML components facilitate understanding of producer-injector relationships, injector dynamic performance, underperformance of patterns in the sector as well as evaluating the impact of different optimization scenarios on incremental oil production. The data-driven production forecast component consists of several ML models and is tailored to assess their impact on oil production of different scenarios such as changes in voidage replacement ratio (VRR) in reservoir, sector, pattern and well levels. Opportunities are also converted into reservoir simulator compatible format in an automated manner to assess the impact of different scenarios using more rigorous numerical methods. The scenarios that yield the highest impact are passed to the field operations team for execution. The solution is expected to serve as a benchmark, upon successful implementation, for optimizing injection schemas in any field or reservoir. The novelty of the system lies in automating the insights generation process, in addition to integrating with an AI/ML production forecasting solution and/or a reservoir simulator to assess different optimization scenarios. It is an end-to-end solution for waterflood optimization because of the integration of various components that allow for the identification and assessment of opportunities all in one environment.

Author(s):  
Gary Sutlieff ◽  
Lucy Berthoud ◽  
Mark Stinchcombe

Abstract CBRN (Chemical, Biological, Radiological, and Nuclear) threats are becoming more prevalent, as more entities gain access to modern weapons and industrial technologies and chemicals. This has produced a need for improvements to modelling, detection, and monitoring of these events. While there are currently no dedicated satellites for CBRN purposes, there are a wide range of possibilities for satellite data to contribute to this field, from atmospheric composition and chemical detection to cloud cover, land mapping, and surface property measurements. This study looks at currently available satellite data, including meteorological data such as wind and cloud profiles, surface properties like temperature and humidity, chemical detection, and sounding. Results of this survey revealed several gaps in the available data, particularly concerning biological and radiological detection. The results also suggest that publicly available satellite data largely does not meet the requirements of spatial resolution, coverage, and latency that CBRN detection requires, outside of providing terrain use and building height data for constructing models. Lastly, the study evaluates upcoming instruments, platforms, and satellite technologies to gauge the impact these developments will have in the near future. Improvements in spatial and temporal resolution as well as latency are already becoming possible, and new instruments will fill in the gaps in detection by imaging a wider range of chemicals and other agents and by collecting new data types. This study shows that with developments coming within the next decade, satellites should begin to provide valuable augmentations to CBRN event detection and monitoring. Article Highlights There is a wide range of existing satellite data in fields that are of interest to CBRN detection and monitoring. The data is mostly of insufficient quality (resolution or latency) for the demanding requirements of CBRN modelling for incident control. Future technologies and platforms will improve resolution and latency, making satellite data more viable in the CBRN management field


Author(s):  
Marcos Faerstein ◽  
Paulo Couto ◽  
José Alves

This paper discusses the impacts that rock wettability may have upon the production and recovery of oil with waterflooding in carbonate reservoirs and how it should be modeled. A broad review of the state of the art has been conducted surveying existing disagreements and knowledge gaps, basic definitions, as well as the correct understanding of the physical phenomena and identification of the characteristics of the various wettability scenarios. Case studies conducted with a black oil reservoir simulator evaluated the impact of different wettability scenarios on oil production and recovery. A comprehensive approach considering all the parameters involved in the wettability modeling was applied to the case studies, showing how the behavior of the reservoir varies as a function of their wettability. This paper shows how relative permeability and capillary pressure should be varied to correctly represent different wettability scenarios and consequently assess its impacts on oil production and recovery. The case studies show that the evaluation of the volume of oil in the reservoir is impacted by wettability through the irreducible water saturation and primary drainage capillary pressure and must be considered in the analyses. In long term analyses, mixed-wet scenarios have a higher oil production and recovery. In medium and short term, the water-wet scenarios have the higher recovery, but in relation to oil production, these scenarios are negatively influenced by the smaller volume of oil in place. The main contribution of this paper is the simultaneous analyses of all the parameters involved in the modeling of wettability showing how they impact the behavior of a reservoir. It shows how the parameters must be varied in a heterogeneous reservoir and how heterogeneity impacts the relevance of wettability in the studies.


Author(s):  
Anik Hanifatul Azizah

[Id]Berkembangnya penggunaan mesin e-voting dan meningkatnya penerapan pemilu dalam jaringan (daring) mengindikasikan bahwa masyarakat percaya akan performansi teknologi informasi dalam meningkatkan proses pemilu. Kesuksesan implementasi teknologi informasi mutlak dibutuhkan, Sebagai dukungan kesuksesan tersebut diperlukan analisis yang mendalam. Sebelum mengimplementasikan teknologi e-voting, pemerintah perlu mengetahui tingkat kesediaan (willingness) masyarakat untuk menggunakan teknologi baru. Tingkatan tertentu bahwa ekspektasi seseorang dapat terpenuhi dengan baik adalah definisi dari kepercayaan (trust). Kepercayaan masyarakat teridentifikasi sebagai faktor utama untuk mempengaruhi niat/ kemauan masyarakat menggunakan sebuah teknologi. Penelitian ini menganalisis pengaruh dari faktor kepercayaan terhadap niat untuk menggunakan e-voting. Penelitian ini mengusulkan sebuah model yang menggambarkan niat masyarakat untuk menggunakan e-voting (Intention to use) dengan mengidentifikasi kepercayaan masyarakat terhadap teknologi (trust of technology). Trust dibagi menjadi beberapa faktor yang lebih spesifik. Kuisioner kertas disebarkan kepada 370 masyarakat negara Indonesia dan 346 di antaranya valid. Kuisioner disebarkan secara langsung oleh surveyor kepada masyarakat yang telah memiliki hak pilih dan disebar secara merata kepada golongan umur yang bervariasi, serta tingkat Pendidikan maupun profesi yang beragam. Hasil penelitian menunjukkan bahwa semakin tinggi Trust of Technology (TOT) dapat meningkatkan niat masyarakat untuk menggunakan e-voting (Intention to Use E-voting - ITU). Ditemukan juga beberapa faktor dapat mempengaruhi pengaruh positif terhadap kepercayaan masyarakat terhadap teknologi. Hasil dari penelitian ini menunjukkan bahwa pemerintah diharapkan untuk memperhatikan fakto-faktor yang mempengaruhi kepercayaan masyarakat yang berujung niat dan kemauan masyarakat untuk menggunakan e-voting sebelum menerapkan e-voting tersebut.Kata Kunci: Kepercayaan, Keinginan, Keamanan, Validitas, Pemilu.[En]Increasing adoption of the electronic voting machine and rising pilot testing of internet voting suggests people believe that ICT can improve the electoral process. Since every new technology adoption needs to achieve successful implementation, deeper analysis on several sides was needed to support it. Before implementing a particular e-voting technology, the government needs to know the level of citizen willingness to adopt those new technologies. The expectancy that promise of an individual or group can be relied upon is defined as trust. The citizen trust can be identified by certain factors that lead to intention to use actual system. This study analyzes the impact of trustworthiness on citizen intention to use e-voting system in a developing country. The research proposes a model of e-voting adoption intention by investigating citizen trustworthiness from trust of technology (TOT). The trust was expanded to more specific unique factors. Offline questionnaires were spreaded to 370 respondents and 346 of them were valid. Questionnaires were distributed directly by surveyors to people who have the right to vote and distributed equally for a wide range of ages, as well as varying levels of education and professions. The results indicate that higher TOT increase citizen intention to use e-voting, and also several key determinants have positive influence on the citizen trust. This result suggested that government should first comply with several factors in citizen trustworthiness before conducting an e-voting system.


2021 ◽  
Vol 156 (Supplement_1) ◽  
pp. S110-S110
Author(s):  
R Odenbrett ◽  
D Ingemansen ◽  
T Baumgart ◽  
V Hieb ◽  
A Ross ◽  
...  

Abstract Introduction/Objective In response to the rapidly evolving COVID-19 pandemic, Sanford Health developed a mobile diagnostic testing program capable of reaching geographically dispersed sites and communities. These mobile laboratories provided on-site testing and sensitive detection of SARS-CoV-2 by leveraging Cepheid’s GeneXpert platform, enabling rapid reporting of results directly to the patient and physician. Aggregation of these results allowed monitoring population infection rates and public health reporting. Methods/Case Report Within 3 weeks of conception, the first mobile unit was designed, engineered and deployed. Key requirements for successful implementation included mobile lab licensure, CLIA certification, COLA enrollment, Quality and Risk assessments, inventory management, lab maintenance and ongoing monitoring. Testing was performed using the Xpert Xpress SARS-CoV-2 test and the population tested were primarily asymptomatic individuals. Results (if a Case Study enter NA) Between May 3rd, 2020 and June 23rd, 2021, a total of 31,148 Xpert Xpress SARS-CoV-2 tests were run across 3 mobile laboratories, with an average of 600 tests performed per week. The percent positivity ranged from 0% to 5.8%, reaching highest positivity in week beginning May 10th, 2020. The average turnaround time from sample collection to result verification was 2.0 hours, and the average time from sample receipt to result verification was under 1 hour. Conclusion Sanford Health’s mobile testing program brings SARS-CoV-2 PCR testing to the community and dramatically reduces the time from sample collection to result reporting compared with traditional testing labs, enabling rapid intervention following a positive result. The flexibility of the GeneXpert platform, including the instrument’s robustness, the independently functioning analyzers, and the wide range of tests available, makes it particularly well suited to mobile laboratories. This program demonstrates the impact of on-site testing and highlights the challenges that were overcome for successful implementation, providing a blueprint to support the development of other mobile laboratories in the US.


2019 ◽  
Vol 59 (1) ◽  
pp. 179
Author(s):  
Stephanie Barakat ◽  
Bob Cook ◽  
Karine D'Amore ◽  
Alberto Diaz ◽  
Andres Bracho

The Moonie onshore oil field discovered in 1961, was the first commercial oil discovery in Australia. The field was purchased by Bridgeport Energy Limited (BEL) from Santos in late 2015. An Australian first initiative by BEL is to enhance oil production from the field using tertiary recovery CO2 miscible flood to maximise field oil recovery. The process involves an evaluation of well injection strategies for a miscible displacement process using reservoir simulation modelling. In addition, the project jointly addresses community concerns regarding the rise in greenhouse gas emissions by sourcing 60000–120000 tonnes/annum of CO2 from a nearby power station and/or an ethanol plant. Justified by laboratory experiments and reservoir compositional simulations, BEL’s project timeline to implement a CO2-enhanced oil recovery (EOR) pilot could start from 2020 followed by a 2–3-year full field oil production acceleration project if additional CO2 can be sourced. Based on incremental recovery and operational consideration, an injection well in the southern end of the field surrounded by six existing producers has been selected as a pilot flood. Positive indicative economics are achieved by the efficient displacement with CO2 of 8000 scf/bbl of incremental oil. Full field dynamic modelling predicts a further 8% oil recovery factor by injecting 60 Bcf of CO2 over five years, which could store in excess of three million tonnes of CO2. For the pilot, more than 90% of the injected CO2 will remain in the Precipice sandstone reservoir. However, the efficiency and viability of a CO2-EOR project is subject to successful implementation of the miscibility modelling, logistics and injection strategy and uncertainty quantification. To propel the project into the execution phase a fast-multiphase reservoir simulator has been implemented to complete a probabilistic range of results in optimal time.


Water Policy ◽  
2009 ◽  
Vol 11 (S1) ◽  
pp. 121-139 ◽  
Author(s):  
Matthew McCartney

Dams, through disruption of physiochemical and biological processes, have water and associated environmental impacts that have far reaching social and economic consequences. The impact of each dam is unique. It depends not only on the dam structure and the attributes of local biota but also climatic and geomorphic conditions. Given the number of existing dams (over 45,000 large dams) and the large number that may be built in the near future, it is clear that humankind must live with the environmental and social consequences for many decades to come. This paper provides a review of the consequences for ecosystems and biodiversity resulting directly from the presence of dams on rivers, and of constraints and opportunities for environmental protection. It illustrates that a wide range of both technical and non-technical measures has been developed to ameliorate the negative impacts of dams. It argues that relatively few studies have been conducted to evaluate the success of these measures and that it is widely perceived that many interventions fail, either for technical reasons or as a consequence of a variety of socio-economic constraints. It discusses the constraints to successful implementation and mechanisms for promoting, funding and ensuring compliance. Finally, it contends that there is a need to improve environmental practices in the operation of both existing and new dams.


2009 ◽  
Vol 8 (1) ◽  
Author(s):  
Chalimah .

eamwork is becoming increasingly important to wide range of operations. It applies to all levels of the company. It is just as important for top executives as it is to middle management, supervisors and shop floor workers. Poor teamwork at any level or between levels can seriously damage organizational effectiveness. The focus of this paper was therefore to examine whether leadership practices consist of team leader behavior, conflict resolution style and openness in communication significantly influenced the team member’s satisfaction in hotel industry. Result indicates that team leader behavior and the conflict resolution style significantly influenced team member satisfaction. It was surprising that openness in communication did not affect significantly to the team members’ satisfaction.


Author(s):  
Nataliya Stoyanets ◽  
◽  
Mathias Onuh Aboyi ◽  

The article defines that for the successful implementation of an innovative project and the introduction of a new product into production it is necessary to use advanced technologies and modern software, which is an integral part of successful innovation by taking into account the life cycle of innovations. It is proposed to consider the general potential of the enterprise through its main components, namely: production and technological, scientific and technical, financial and economic, personnel and actual innovation potential. Base for the introduction of technological innovations LLC "ALLIANCE- PARTNER", which provides a wide range of support and consulting services, services in the employment market, tourism, insurance, translation and more. To form a model of innovative development of the enterprise, it is advisable to establish the following key aspects: the system of value creation through the model of cooperation with partners and suppliers; creating a value chain; technological platform; infrastructure, determine the cost of supply, the cost of activities for customers and for the enterprise as a whole. The system of factors of influence on formation of model of strategic innovative development of the enterprise is offered. The expediency of the cost of the complex of technological equipment, which is 6800.0 thousand UAH, is economically calculated. Given the fact that the company plans to receive funds under the program of socio-economic development of Sumy region, the evaluation of the effectiveness of the innovation project, the purchase of technological equipment, it is determined that the payback period of the project is 3 years 10 months. In terms of net present value (NPV), the project under study is profitable. The project profitability index (PI) meets the requirements for a positive decision on project implementation> 1.0. The internal rate of return of the project (IRR) also has a positive value of 22% because it exceeds the discount rate.


2021 ◽  
Author(s):  
Ekaterina Mosolova ◽  
Dmitry Sosin ◽  
Sergey Mosolov

During the COVID-19 pandemic, healthcare workers (HCWs) have been subject to increased workload while also exposed to many psychosocial stressors. In a systematic review we analyze the impact that the pandemic has had on HCWs mental state and associated risk factors. Most studies reported high levels of depression and anxiety among HCWs worldwide, however, due to a wide range of assessment tools, cut-off scores, and number of frontline participants in the studies, results were difficult to compare. Our study is based on two online surveys of 2195 HCWs from different regions of Russia during spring and autumn epidemic outbreaks revealed the rates of anxiety, stress, depression, emotional exhaustion and depersonalization and perceived stress as 32.3%, 31.1%, 45.5%, 74.2%, 37.7% ,67.8%, respectively. Moreover, 2.4% of HCWs reported suicidal thoughts. The most common risk factors include: female gender, nurse as an occupation, younger age, working for over 6 months, chronic diseases, smoking, high working demands, lack of personal protective equipment, low salary, lack of social support, isolation from families, the fear of relatives getting infected. These results demonstrate the need for urgent supportive programs for HCWs fighting COVID-19 that fall into higher risk factors groups.


Author(s):  
Sergei Soldatenko ◽  
Sergei Soldatenko ◽  
Genrikh Alekseev ◽  
Genrikh Alekseev ◽  
Alexander Danilov ◽  
...  

Every aspect of human operations faces a wide range of risks, some of which can cause serious consequences. By the start of 21st century, mankind has recognized a new class of risks posed by climate change. It is obvious, that the global climate is changing, and will continue to change, in ways that affect the planning and day to day operations of businesses, government agencies and other organizations and institutions. The manifestations of climate change include but not limited to rising sea levels, increasing temperature, flooding, melting polar sea ice, adverse weather events (e.g. heatwaves, drought, and storms) and a rise in related problems (e.g. health and environmental). Assessing and managing climate risks represent one of the most challenging issues of today and for the future. The purpose of the risk modeling system discussed in this paper is to provide a framework and methodology to quantify risks caused by climate change, to facilitate estimates of the impact of climate change on various spheres of human activities and to compare eventual adaptation and risk mitigation strategies. The system integrates both physical climate system and economic models together with knowledge-based subsystem, which can help support proactive risk management. System structure and its main components are considered. Special attention is paid to climate risk assessment, management and hedging in the Arctic coastal areas.


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