Lessons Learned from Schedule Estimation Using Real-Time Data in a Concreting Operation

Abstract Natural gas has become one of the major sources of energy for homes, public buildings and businesses, therefore gas storage is particularly important to ensure continuous provision compensating the differences between supply and demand. Stogit, part of Snam group, has been carrying out gas storage activities since early 1960's. Natural gas is usually stored underground, in large storage reservoirs. The gas is injected into the porous rock of depleted reservoirs bringing the reservoir nearby to its original condition. Injected gas can be withdrawn depending on the need. Gas market demands for industries and homes in Italy are mostly guaranteed from those Stogit reservoirs even in periods when imports are in crisis. Typically, from April to October, the gas is injected in these natural reservoirs that are "geologically tested"; while from November to March, gas is extracted from the same reservoirs and pumped into the distribution networks to meet the higher consumer demand. Thirty-eight (38) wells, across nine (9) depleted fields, are completed with downhole quartz gauges and some of them with fiber-optics gauges. Downhole gauges are installed to continuously measure and record temperature and pressure from multiple reservoirs. The Real Time data system installed for 29 wells is used to collect, transmit and make available downhole data to Stogit (Snam) headquarter office. Data is automatically collected from remote terminal units (RTUs) and transferred over Stogit (Snam) network. The entire system works autonomously and has the capability of being remotely managed from anywhere over the corporate Stogit (Snam) IT network. Historical trends, including fiber optics gauges ones, are visualized and data sets could be retrieved using a fast and user-friendly software that enables data import into interpretation and reservoir modeling software. The use of this data collection and transmission system, versus the traditional manual download, brought timely data delivery to multiple users, coupled with improved personnel safety since land travels were eliminated. The following pages describe the case study, lessons learned, and integrated new practices used to improve the current and future data transmission deployments.

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Current measurements from a deep real-time metocean mooring: lessons learned on real-time data QA/QC

2015 IEEE/OES Eleveth Current, Waves and Turbulence Measurement (CWTM) ◽

10.1109/cwtm.2015.7098133 ◽

2015 ◽

Author(s):

B. A. Magnell ◽

L. I. Ivanov ◽

A. T. Morrison ◽

E. G. Hasbrouck

Keyword(s):

Real Time ◽

Lessons Learned ◽

Time Data ◽

Real Time Data

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Inline Drilling Fluid Property Measurement, Integration, and Modeling to Enhance Drilling Practice and Support Drilling Automation

10.2118/208064-ms ◽

2021 ◽

Author(s):

Sanjit Roy ◽

Saiyid Z. Kamal ◽

Richard Frazier ◽

Ross Bruns ◽

Yahia Ait Hamlat

Keyword(s):

Real Time ◽

Drilling Fluid ◽

Measurement Data ◽

Lessons Learned ◽

Valuable Insight ◽

Drilling Process ◽

Time Data ◽

Fluid Property ◽

Real Time Data ◽

Fluid Properties

Abstract Frequent, reliable, and repeatable measurements are key to the evolution of digitization of drilling information and drilling automation. While advances have been made in automating the drilling process and the use of sophisticated engineering models, machine learning techniques to optimize the process, and lack of real-time data on drilling fluid properties has long been recognized as a limiting factor. Drilling fluids play a significant function in ensuring quality well construction and completion, and in-time measurements of relevant fluid properties are key to automation and enhancing decision making that directly impacts well operations. This paper discusses the development and application of a suite of automated fluid measurement devices that collect key fluid properties used to monitor fluid performance and drive engineering analyses without human involvement. The deployed skid-mounted devices continually and reliably measure properties such as mud weight, apparent viscosity, rheology profiles, temperatures, and emulsion stability to provide valuable insight on the current state of the fluid. Real-time data is shared with relevant rig and office- based personnel to enable process monitoring and trigger operational changes. It feeds into real-time engineering analyses tools and models to monitor performance and provides instantaneous feedback on downhole fluid behavior and impact on drilling performance based on current drilling and drilling fluid property data. Equipment reliability has been documented and demonstrated on over 30 wells and more than 400 thousand ft of lateral sections in unconventional shale drilling in the US. We will share our experience with measurement, data quality and reliability. We will also share aspects of integrating various data components at disparate time intervals into real-time engineering analyses to show how real-time measurements improve the prediction of well and wellbore integrity in ongoing drilling operations. In addition, we will discuss lessons learned from our experience, further enhancements to broaden the scope, and the integration with operators, service companies and other original equipment manufacturer in the domain to support and enhance the digital drilling ecosystem.

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Developing a smartphone app with UK migrants for UK migrants: lessons learned from focus group work

European Journal of Public Health ◽

10.1093/eurpub/ckaa166.033 ◽

2020 ◽

Vol 30 (Supplement_5) ◽

Author(s):

R Burns ◽

G C G Hugenholtz ◽

V Kirkby ◽

N Elsay ◽

R W Aldridge

Keyword(s):

Data Collection ◽

Real Time ◽

Well Being ◽

Lessons Learned ◽

Migrant Population ◽

Time Data ◽

Longitudinal Data Collection ◽

Real Time Data ◽

The Uk ◽

App Design

Abstract Background In 2018, 14% of people living in the UK were born abroad, yet we have a limited understanding of the broader determinants of their health. To address this knowledge gap, the Health on the MovE (HOME) smartphone application (app) study was conceived. Through app-based surveys, the study will examine how risk factors for health and well-being are distributed among migrants and how these vary over time since migration to the UK. There is a lack of research addressing the development of apps for longitudinal data collection in the general population - and we did not find any in migrant groups. Methods To better inform the design of the HOME app study, three workshops were held in 2018 and 2019, involving both migrants and App development experts. We used a semi-structured interview schedule focused on five themes: smartphones, apps and research, HOME app wireframe (screen-by-screen review of the app), types of surveys and survey schedules, resource section content, and participant engagement strategies. The participants were purposively sampled to reflect the migrant population arriving in the UK from non-EU countries. Results Migrants reported high smartphone use and were positive about the app design and app-based research. Concerns around privacy and data protection were highlighted and limits were suggested for the frequency of surveys and the number of questions used. Mental health was identified as a key topic for research. Participants requested the inclusion of resources concerning asylum claim procedures and immigrant and labour laws. Migrants advised that study recruitment material should clearly state the purpose and scope of the research and requested regular feedback on study outcomes. Conclusions The workshops provided important feedback and facilitated the co-production of the HOME app. Overall findings suggest that the study would be both acceptable to the migrant population and feasible for real-time data collection. Key messages The process identified potential barriers to the acceptability and feasibility of an app-based study for real-time data collection in the UK migrant population. Organising workshops with migrants allowed for an iterative process of co-production of the HOME app. Their critical comments resulted in subsequent changes to the app design and study methodology.

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