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The Society of Exploration Geophysicists (SEG) Scholarships encourage the study of geophysics and related geosciences in universities around the world. Applications accepted 1 November to 1 March annually. Support SEG Scholarships Your donations help provide opportunities to future geophysicists. Thanks to the generosity of our donors, the SEG offers a range of different scholarship opportunities to students all over the globe. Scholarships range from US$500 to US$10,000 per academic year; average awards are approximately US$3,200.
- Asia (1.00)
- Africa > Middle East (0.18)
Abstract Objective/Scope: The purpose of this paper is to study how UEP has implemented Field Production and Maintenance Trainee Programs. It will further evaluate the effectiveness of the program and how it has benefited the local community and the company. Methods, Procedures, Process: UEP's Field Trainee program provides opportunities for young people from the concession in which UEP operates. It creates jobs for local youth to get trained and work in the oil and gas sector. The process to recruit the local and train them is extremely rigorous. The applications are invited via placing an advertisement in the local newspapers. Candidates meeting the criteria, undergo a rigorous test and interview process. Candidates shortlisted on merit are selected. The training of selected local high school graduates is initially performed in the classroom by senior faculty of renowned local Sindh university. After completing classroom training, they embark on an on-the-job training plan under the supervision of seasoned industry professionals. Results, Observations, Conclusion: Over many decades the UEP trainee program has developed skillset of the locals and has given them employment opportunity. It has provided a talent pipeline for the organization and helped UEP give back to the community as part of its commitment. Several senior positions at UEP are occupied by employees inducted through this program. Some of them are working for other multinational organizations in Pakistan and abroad. Apart from developing the talent pool, this program has increased organization's brand value especially amongst the locals and has helped the organization forge meaningful relationship with the local community. Novel/Additive Information: This program has been a great success story for UEP. It shows that benefits are not limited to meeting the workforce requirement. Other organizations in Pakistan and abroad can learn from UEP's success and may introduce similar programs. This program is mainly focused on hiring resources for Operations functions. Going forward, the need for introducing similar program for other functions can be evaluated.
Back again with an all-virtual format, the 6th edition of the SPE Startup Village has opened for applications for its Energy Startup Competition to be held on 20โ21 September. Tuesday's pitch competition will showcase emerging technologies from across the energy spectrum and five winners will receive cash prizes. They will also gain high-value exposure to potential investors. Following the 15 July application deadline, a dozen finalist companies will be invited to mentoring sessions ahead of the big pitch day and will receive a complimentary registration to the SPE Annual Technical Conference and Exhibition (ATCE) in Houston on 3โ5 October. At the virtual event, entrepreneurs will be given 5โ7 minutes to explain what their company does to a panel of venture capitalists, angel investors, and industry technology leaders.
- Contests & Prizes (0.46)
- Personal > Honors (0.42)
- Banking & Finance > Trading (0.80)
- Energy > Oil & Gas > Upstream (0.62)
Abstract Employers commonly use time-consuming screening tools or online matching engines that are driven by manual roles and predefined keywords, to search for potential job applicants. Such traditional techniques have not kept pace with the new digital revolution in machine learning and big data analytics. This paper presents advanced artificial intelligent solutions employed for ranking resumes and CV-to-Job Description matching. Open source resumes and job descriptions' documents were used to construct and validate the machine learning models in this paper. Documents were converted to images and processed via Google cloud using Optical Character Recognition algorithm (OCR) to extract text information from all resumes and job descriptions' documents, with more than 97% accuracy. Prior to modeling, the extracted text were processed via a series of Natural Language Processing (NLP) techniques by splitting/tokenizing common words, grouping together inflected form of words, i.e. lemmatization, and removal of stop words and punctuation marks. After text processing, resumes were trained using the unsupervised machine learning algorithm, Latent Dirichlet Allocation (LDA), for topic modeling and categorization. Given the type of resumes used, the algorithm was able to categorize them into 4 main job sectors: marketing and business, engineering, computer science/IT and health. Scores were assigned to each resume to represent the maximum LDA probability for ranking. Another more advanced deep learning algorithm, called Doc2Vec, was also used to train and match potential resumes to relevant job descriptions. In this model, resumes are represented by unique vectors that can be used to group similar documents, match and retrieve resumes related to a given job description document provided by HR. The similarity is measured between each resume and the given job description file to query the top job candidates. The model was tested against several job description files related to engineering, IT and human resources, and was able to identify the top-ranking resumes from over hundreds of trained resumes. This paper presents an innovative method for processing, categorizing and ranking resumes using advanced computational models empowered by the latest fourth industrial resolution technologies. This solution is beneficial to both job seekers and employers, providing efficient and unbiased data-driven method for finding top applicants for a given job.
We know that predictive models developed by artificial-intelligence (AI) and machine-learning (ML) algorithms are based on data. And, because we know how this data is used to build AI-based models, the main target of AI ethics is addressing how AI models become biased based on the quality and the quantity of the data that is used. This first part of this two-part series discusses the nonengineering applications of AI and ML and how human biases such as racism and sexism can be included in AI models through the inclusion of biased data during the training of the algorithms. Because engineering applications of AI and ML are used to model physical phenomena, Part 2 of the series will discuss how AI ethics can determine and clarify how human biases of traditional engineers--assumptions, interpretations, simplifications, and preconceived notions--can be revealed in the engineering applications of AI and ML. Introduction The reasons nuclear weapons did not end up destroying our planet (at least so far) had much to do with worldwide treaties and agreements on how to handle nuclear bombs.
- Energy > Oil & Gas (0.98)
- Government (0.67)
The signals coming from the price of oil and gas are getting brighter, but Texas producers don't seem to have noticed. Oilfield activity in Texas and nearby states dipped in the current quarter, according to a recently released survey by the Federal Reserve Bank of Dallas, which nonetheless described the activity as strong and solid. Based on responses to the survey from leaders in the exploration and production (E&P) and service sectors, price expectations are not much below the currently high market prices. That would have inspired rapid growth a few years ago. For now, however, the E&P and service sectors show no signs of diverging from plans to maximize profits rather than focus on growth.
- Energy > Oil & Gas > Upstream (1.00)
- Banking & Finance > Economy (1.00)
- Government > Regional Government > North America Government > United States Government (0.90)
- North America > United States > Texas > Permian Basin > Yeso Formation (0.99)
- North America > United States > Texas > Permian Basin > Yates Formation (0.99)
- North America > United States > Texas > Permian Basin > Wolfcamp Formation (0.99)
- (21 more...)
We know that predictive models developed by artificial-intelligence (AI) and machine-learning (ML) algorithms are based on data. And, because we know how this data is used to build AI-based models, the main target of AI ethics is addressing how AI models become biased based on the quality and the quantity of the data that is used. This first part of this two-part series discusses the nonengineering applications of AI and ML and how human biases such as racism and sexism can be included in AI models through the inclusion of biased data during the training of the algorithms. Because engineering applications of AI and ML are used to model physical phenomena, Part 2 of the series will discuss how AI ethics can determine and clarify how human biases of traditional engineers--assumptions, interpretations, simplifications, and preconceived notions--can be revealed in the engineering applications of AI and ML. Introduction The reasons nuclear weapons did not end up destroying our planet (at least so far) had much to do with worldwide treaties and agreements on how to handle nuclear bombs.
- Energy > Oil & Gas (0.98)
- Government (0.67)
Abstract The Department of Petroleum Resources, Nigeria's oil and gas industry regulator, is an opportunity provider and business enabler. Using regulatory instruments such as Licenses, Approvals and Permits, the Department has enabled investors to unlock opportunities in the Upstream, Midstream and Downstream sectors of the industry. The Oil and Gas Industry Service Permit (OGISP) is a mandatory requirement for all service providers rendering or engaged to render technical service to the industry, in accordance with section 60A of the amended Petroleum (Drilling & Production) Regulations, 1988. Since its establishment, the Department has issued over a million permits to service providers in various areas of specialization. This paper examines the OGISP system framework; OGISP application process and requirements for permit issuance; benefits of OGISP to the industry and the Nigerian economy; and recommendations to improve the OGISP system.
Abstract The Leading Edge accepts classified advertising if it is related to applied geosciences.
- Asia > Middle East > Israel > Mediterranean Sea (0.26)
- Asia > Middle East > Saudi Arabia > Eastern Province > Dhahran (0.20)
SPE provides opportunities for professionals to enhance their technical and professional competence. Credentialing is one way for individuals to demonstrate their technical knowledge and dedication to their profession. In 2004, SPE developed the Petroleum Engineering Certification Program for members to achieve recognition of their technical and professional achievements through examination in the form of an international credential. This is of particular benefit to members in regions and countries that do not have credentialing programs for petroleum engineers. "The certification exam is targeted to areas of the world that do not have government licensing bodies to regulate the practice of engineering in that country," said Byron Haynes Jr., development planning team leader for Petroleum Development Oman, and chairperson of the SPE Petroleum Engineering Certification Committee.