“The Digital Oilfield” : Using IoT to reduce costs in an era of decreasing oi...Karthikeyan Rajamanickam
Executive Summary:
oWe decided to create this point-of-view after seeing many abstract presentations and esoteric concepts on Digital Oilfield, IoT, Big Data and Analytics.
oThis is our attempt to bring a practical implementation view to IoT by combining Digital Oilfield and IoT.
oHere, we also envisage sharing our IoT experience and lessons learnt in implementing Digital Oilfield solutions around IoT.
oThe following comprise our fundamental business case for Finance:
oPRODUCTION FORECAST
oFAULT COMPARTMENTS
oWELL LOCATION OPTIMIZATION
Introduction to Project Economics in Oil and Gas Exploration and Production (Upstream) Industry, including basic project economics method and example of calculation.
Integrated Oil Field Development Plan - FDP. Criteria, strategy and process f...Giuseppe Moricca
Integrated Oil Field Development Plan - FDP.
The integrated oil field development plan describes process, explores options, and targets, aimed at the optimal oil and gas field development in line with the oil company strategy.
The spine in the process is the specialist teams who navigate, manage and integrate the subsurface and surface complexities, uncertainties and opportunities into a single development plan, maximizing the overall field recovery and asset value.
“The Digital Oilfield” : Using IoT to reduce costs in an era of decreasing oi...Karthikeyan Rajamanickam
Executive Summary:
oWe decided to create this point-of-view after seeing many abstract presentations and esoteric concepts on Digital Oilfield, IoT, Big Data and Analytics.
oThis is our attempt to bring a practical implementation view to IoT by combining Digital Oilfield and IoT.
oHere, we also envisage sharing our IoT experience and lessons learnt in implementing Digital Oilfield solutions around IoT.
oThe following comprise our fundamental business case for Finance:
oPRODUCTION FORECAST
oFAULT COMPARTMENTS
oWELL LOCATION OPTIMIZATION
Introduction to Project Economics in Oil and Gas Exploration and Production (Upstream) Industry, including basic project economics method and example of calculation.
Integrated Oil Field Development Plan - FDP. Criteria, strategy and process f...Giuseppe Moricca
Integrated Oil Field Development Plan - FDP.
The integrated oil field development plan describes process, explores options, and targets, aimed at the optimal oil and gas field development in line with the oil company strategy.
The spine in the process is the specialist teams who navigate, manage and integrate the subsurface and surface complexities, uncertainties and opportunities into a single development plan, maximizing the overall field recovery and asset value.
WHY IS A RESERVES DEFINITION NEEDED?;
Classification Framework; Proven Reserves; Unproven reserves; Resources; RESERVES UNCERTAINTY CATEGORIES; PROJECT MATURITY SUB-CLASSES; PETROLEUM RESOURCES CLASSIFICATION BASED ON PROJECT STAGESOIL AND GAS PROJECT EVALUATION STAGES; OIL AND GAS PROJECT EVALUATION; PROJECT EVALUATION ; PROBABILITY OF SUCCESS (POSG)
Oil 101 - A Free Introduction to Oil and Gas
What is Downstream Oil and Gas?
Processing, transporting and selling refined products made from crude oil is the business of the downstream segment of the oil and gas industry.
Key downstream business sectors include:
Oil Refining
Supply and Trading
Product Marketing and Retail
The downstream industry provides thousands of products to end-user customers around the globe.
Many products are familiar such as gasoline, diesel, jet fuel, heating oil and asphalt for roads. Others are not as familiar such as lubricants, synthetic rubber, plastics, fertilizers and pesticides.
A brief summary of Oil and Gas Upstream. PPT includes basic Chemistry, Basic Geology, Oil formation, Migration of Petroleum, Reservoir, porosity, permeability, Geological structures for petroleum entrapment, Exploration methods, Geological methods, Geophysical methods, geophysical methods, seismic methods, seismic methods, gravity methods, magnetic methods, well drilling, preparation to drill, setting the rig, drilling, enhanced oil recovery, EOR, primary oil recovery, secondary oil recovery, thermal recovery, gas injection and chemical injection
Be a part of the modern world by integrating digital technologies in the Oil & Gas operations. It will not only keep you digitally connected but also reduce the cost and risk involved in day-to-day industry activities. Download our free copy of whitepaper: https://www.bluemailmedia.com/oil-gas-a-definitive-path-towards-digitalization.php
Data as the New Oil: Producing Value in the Oil and Gas IndustryVMware Tanzu
Oil and gas exploration and production activities generate large amounts of data from sensors, logistics, business operations and more. Given the data volume, variety and velocity, gaining actionable and relevant insights from the data is challenging. Learn about these challenges and how to address them by leveraging big data technologies in this webinar.
During the webinar we will dive deep into approaches for predicting drilling equipment function and failure, a key step towards zero unplanned downtime. In the process of drilling wells, non-productive time due to drilling equipment failure can be expensive. We will highlight how the Pivotal Data Labs team uses big data technologies to build models for predicting drilling equipment function and failure. Models such as these can be used to build essential early warning systems to reduce costs and minimize unplanned downtime.
Panelist:
Rashmi Raghu, Senior Data Scientist, Pivotal
Hosted by:
Tim Matteson, Co-Founder -- Data Science Central
Video replay is available to watch here: http://youtu.be/dhT-tjHCr9E
IIoT + Predictive Analytics: Solving for Disruption in Oil & Gas and Energy &...DataWorks Summit
The electric grid has evolved from linear generation and delivery to a complex mix of renewables, prosumer-generated electricity, and electric vehicles (EVs). Smart meters are generating loads of data. As a result, traditional forecasting models and technologies can no longer adequately predict supply and demand. Extreme weather, an aging infrastructure, and the burgeoning worldwide population are also contributing to increased outage frequency.
In oil and gas, commodity pricing pressures, resulting workforce reductions, and the need to reduce failures, automate workflows, and increase operational efficiencies are driving operators to shift analytics initiatives to advanced data-driven applications to complement physics-based tools.
While sensored equipment and legacy surveillance applications are generating massive amounts of data, just 2% is understood and being leveraged. Operationalizing it along with external datasets enables a shift from time-based to condition-based maintenance, better forecasting and dramatic reductions in unplanned downtime.
The session includes plenty of real-world anecdotes. For example, how an electric power holding company reduced the time it took to investigate energy theft from six months to less than one hour, producing theft leads in minutes and an expected multi-million dollar ROI. How a global offshore contract drilling services provider implemented an open source IIoT solution across its fleet of assets in less than a year, enabling remote monitoring, predictive analytics and maintenance.
Key takeaways:
• How are new processes for data collection, storage and democratization making it accessible and usable at scale?
• Beyond time series data, what other data types are important to assess?
• What advantage are open source technologies providing to enterprises deploying IIoT?
• Why is collaboration important across industrial verticals to increase IIoT open source adoption?
Speaker
Kenneth Smith, General Manager, Energy, Hortonworks
Le 05 Liquefied Natural Gas (LNG) BusinessNsulangi Paul
This module describes natural gas business globally. Gives details explanation on various activities connected to this liquid energy business as such LNG value chain, structures, factors to consider on capacity, number of facilities and expected global LNG business.
WHY IS A RESERVES DEFINITION NEEDED?;
Classification Framework; Proven Reserves; Unproven reserves; Resources; RESERVES UNCERTAINTY CATEGORIES; PROJECT MATURITY SUB-CLASSES; PETROLEUM RESOURCES CLASSIFICATION BASED ON PROJECT STAGESOIL AND GAS PROJECT EVALUATION STAGES; OIL AND GAS PROJECT EVALUATION; PROJECT EVALUATION ; PROBABILITY OF SUCCESS (POSG)
Oil 101 - A Free Introduction to Oil and Gas
What is Downstream Oil and Gas?
Processing, transporting and selling refined products made from crude oil is the business of the downstream segment of the oil and gas industry.
Key downstream business sectors include:
Oil Refining
Supply and Trading
Product Marketing and Retail
The downstream industry provides thousands of products to end-user customers around the globe.
Many products are familiar such as gasoline, diesel, jet fuel, heating oil and asphalt for roads. Others are not as familiar such as lubricants, synthetic rubber, plastics, fertilizers and pesticides.
A brief summary of Oil and Gas Upstream. PPT includes basic Chemistry, Basic Geology, Oil formation, Migration of Petroleum, Reservoir, porosity, permeability, Geological structures for petroleum entrapment, Exploration methods, Geological methods, Geophysical methods, geophysical methods, seismic methods, seismic methods, gravity methods, magnetic methods, well drilling, preparation to drill, setting the rig, drilling, enhanced oil recovery, EOR, primary oil recovery, secondary oil recovery, thermal recovery, gas injection and chemical injection
Be a part of the modern world by integrating digital technologies in the Oil & Gas operations. It will not only keep you digitally connected but also reduce the cost and risk involved in day-to-day industry activities. Download our free copy of whitepaper: https://www.bluemailmedia.com/oil-gas-a-definitive-path-towards-digitalization.php
Data as the New Oil: Producing Value in the Oil and Gas IndustryVMware Tanzu
Oil and gas exploration and production activities generate large amounts of data from sensors, logistics, business operations and more. Given the data volume, variety and velocity, gaining actionable and relevant insights from the data is challenging. Learn about these challenges and how to address them by leveraging big data technologies in this webinar.
During the webinar we will dive deep into approaches for predicting drilling equipment function and failure, a key step towards zero unplanned downtime. In the process of drilling wells, non-productive time due to drilling equipment failure can be expensive. We will highlight how the Pivotal Data Labs team uses big data technologies to build models for predicting drilling equipment function and failure. Models such as these can be used to build essential early warning systems to reduce costs and minimize unplanned downtime.
Panelist:
Rashmi Raghu, Senior Data Scientist, Pivotal
Hosted by:
Tim Matteson, Co-Founder -- Data Science Central
Video replay is available to watch here: http://youtu.be/dhT-tjHCr9E
IIoT + Predictive Analytics: Solving for Disruption in Oil & Gas and Energy &...DataWorks Summit
The electric grid has evolved from linear generation and delivery to a complex mix of renewables, prosumer-generated electricity, and electric vehicles (EVs). Smart meters are generating loads of data. As a result, traditional forecasting models and technologies can no longer adequately predict supply and demand. Extreme weather, an aging infrastructure, and the burgeoning worldwide population are also contributing to increased outage frequency.
In oil and gas, commodity pricing pressures, resulting workforce reductions, and the need to reduce failures, automate workflows, and increase operational efficiencies are driving operators to shift analytics initiatives to advanced data-driven applications to complement physics-based tools.
While sensored equipment and legacy surveillance applications are generating massive amounts of data, just 2% is understood and being leveraged. Operationalizing it along with external datasets enables a shift from time-based to condition-based maintenance, better forecasting and dramatic reductions in unplanned downtime.
The session includes plenty of real-world anecdotes. For example, how an electric power holding company reduced the time it took to investigate energy theft from six months to less than one hour, producing theft leads in minutes and an expected multi-million dollar ROI. How a global offshore contract drilling services provider implemented an open source IIoT solution across its fleet of assets in less than a year, enabling remote monitoring, predictive analytics and maintenance.
Key takeaways:
• How are new processes for data collection, storage and democratization making it accessible and usable at scale?
• Beyond time series data, what other data types are important to assess?
• What advantage are open source technologies providing to enterprises deploying IIoT?
• Why is collaboration important across industrial verticals to increase IIoT open source adoption?
Speaker
Kenneth Smith, General Manager, Energy, Hortonworks
Le 05 Liquefied Natural Gas (LNG) BusinessNsulangi Paul
This module describes natural gas business globally. Gives details explanation on various activities connected to this liquid energy business as such LNG value chain, structures, factors to consider on capacity, number of facilities and expected global LNG business.
Practical thoughts for cloud transformationMark Osborn
A look at how to get beyond the 20% of workloads cloud adoption barrier with IBM's app transformation approach. Check out www.ibm.com/cloud/garage/adoption and https://www.ibm.com/cloud/garage/content/field-guide/app-modernization-field-guide/
Data Center of the Future: Designing a modernized, high performance computing...Capgemini
With cloud being hailed as the new black, customers are increasingly looking to easily leverage Hybrid Cloud and Hyper-Converged Architecture, without transformation in technology. At VMworld US 2019, Eric Killinger, Director, IT strategy, Capgemini NA, spoke about how Capgemini makes cloud run better by simplifying infrastructure for your existing landscape via a software-defined data center, supporting immediate OPEX savings, real-time data processing and cloud-based scalability and cost predictability, illustrating the joint success with VMware of such a rollout at Hydro One.
A Journey to a Serverless Business Intelligence, Machine Learning and Big Dat...DataWorks Summit
In this talk we will describe the journey we made with one of our customers, Volotea, to deploy a serverless Business Intelligence (BI), Machine Learning (ML) and Big Data (BD) platform on the Cloud. The new platform leverages Platform-as-a-Service (PaaS) Cloud services, and it is the result of the reengineering and extension of an existing platform based on Cloud Infrastructure-as-a-Service (IaaS) services and bare-metal systems. Managing and maintaining BI, ML and BD platforms based on bare-metal or IaaS deployments is not a straightforward task, and as size and complexity grow, we often find ourselves spending more and more time in tasks that are rather administrative, more than of a development or analytics nature. That is exactly what Volotea realized, and together we envisioned and executed a plan to lift and reengineer their platform into a new solution that leverages Microsoft Azure PaaS services. We have delivered a solution that manages to greatly reduce the administrative burden as well as the technical complexity when implementing new use cases. The new platform is based on the Microsoft Azure stack and it includes Azure Data Lake, Azure Data Lake Analytics, Azure Data Factory, Azure Machine Learning and Azure SQL Database. Join us in this talk where we will share our lessons learned and we will discuss how to plan and execute such an endeavor.
Learn how to make smart assets to improve operational efficiencies.
Capitalize on the value of IoT tank monitoring solutions and improve your organization's visibility, actionability, and profitability.
An overview of what it is and how it can benefit your operations. Enterprise Asset Management (EAM) is the lifecycle management of the physical assets of an organization. An asset can be such things as machines, equipment, tools, buildings, plants, vehicles or ships.
Try IBM Maximo today: https://www.ibm.com/us-en/marketplace/maximo
Cambashi Industrial IoT introduction at Connect event 2017.06.21CambashiLtd
Alan Griffiths of Cambashi introduced the Industrial IoT at The Manufacturer's Connect event in June 2017. It describes what's new in IIoT, who's doing what and why you should be planning a project.
How IBM is helping developers win the race to innovate with next-gen cloud se...Michael Elder
In the race to transform, enterprises employ cloud to deliver innovation and stay ahead of the competition. New services are built natively on cloud, but what about the 80% of enterprise applications that have not yet moved to the cloud.
In this session, we'll answer these questions: How do I integrate next-gen technology like Blockchain, Watson IoT, and Data &AI into my new applications? How do I make multicloud an advantage instead of adding new complexity?
Covid-19 Massive Retrenchment and Unemployment: Individuals Upskilling & Resk...Anthony Ng
REE LIVE WEBINAR
Covid-19 Massive Retrenchment and Unemployment: Individuals Upskilling & Reskilling Training towards IR4.0 Digital Transformation
Join & Find out from Experts Industries Players Opinions by
✅1. YBhg. Dato’ Mohd Sahar Bin Darusman – Chief Employment Insurance Office of PERKESO
✅2. Mr. Ab Rahim Yusoff- Deputy Director General of Malaysia Productivity Corporation (MPC)
✅3. Dato’ Palaniappan Joseph - Chairman of Federation of Malaysian Manufacturers (FMM) TVET & Future Skills Committee ASEAN Future Workforce Council
✅4. Mr. Nizmar Mohd Nazar – Chief Information Officer of Malaysia Automotive Robotics and IOT Institute (MARII)
✅5. Dr. M Shahrul Azmi M Yusoff - Director of SIRIM Berhad (Innovation Centre of Innovation in Smart Manufacturing)
Moderated by Anthony Ng, CEO of MIT Academy Sdn Bhd
Date: 27 April 2020, Monday
Time: 3.00pm to 4.30pm (Malaysian Time GMT+8)
Free Registration Link: http://bit.ly/COVID19MIT
(FREE Live Admission for Everyone)
Target Audience : Multinational Companies (MNC), Small Medium Enterprises (SME), Government Departments, Engineers & Technicians, Colleges and Universities Lecturers/Post Graduates in Engineering & Technical Fields, Retrenched and Unemployed Individuals.
ℹ️ For any enquiry, kindly WhatsApp +60123831864, http://wa.me/60123831864
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas