Esri 2019 Petroleum User Group, London

Equinor goes green with GIS. GIS ‘at heart of digital transformation’. GIS and real time production data. Notebook Server for data scientists. ExxonMobil’s major GIS-for-BIM deployment. Pipeline ‘GIS in GIS’. Survey 123 and Borealis for seismic stakeholder engagement (Tullow). Esri big data toolkit. WoodMac blends AI/ML with GIS. Shell on GIS-enabled exploration. ExxonMobil on GIS data quality. Orbital Insight on GIS-enabled intel. IOGP offshore infrastructure survey data model. UKCS as a ‘data-driven basin’. Neftex on ArcGIS interop extension, on PostGIS and QuickPlates. 40Geo’s Raptor Geo-IoT.

In her keynote address, Elena Farnè described Equinor’s sideways move into offshore wind. While current energy scenarios out to 2050 show that large oil and gas investments are needed, (‘reassuring for us in oil and gas’) the resulting CO2 emissions remain far from a 2° scenario. The floating offshore wind market has a potential of 12GW by 2030. Currently, the largest is Dudgeon at 402MW. The planned Dogger Bank installation will be the biggest in the world. The Hywind demonstrator between Snorre and Gulfaks produces 88MW of electrical power for offshore oilfields. In the Q&A Farnè was asked about competing demands for capital between oil and gas and wind. Equinor plans to devote 15-20% of CAPEX to renewables i.e. one Dogger Bank sized project per year.

Matt Ballard (Esri) continued with the going green theme, presenting new functionality in ArcGIS Pro such as pie charts of EU renewables, graphs of growth in solar and a ‘Living Atlas’ of windfarms in Germany. A geospatial workflow for windfarm location leveraged DTN data on windspeeds into another ArcGIS Living Atlas, incorporating distance from shore, shipping lanes, water depth and infrastructure. Other functions of note are a 3D visual impact assessment and ‘viewshed analysis’ i.e. what can be seen from where. The green functionality is delivered (broadly) from one of Esri’s Operations Dashboards and also from third-party Getech/Exprodat as ArcGIS for Renewables, built with the JavaScript API.

Dal Hunter (Esri) puts GIS at the heart of the digital transformation. Web GIS allows all data types to be consolidated in the geospatial cloud and system of record. Data can be fed to multiples stakeholders including ‘non-GIS people’. Esri has previously shied away from development, but the operations dashboards are changing this, making real time IoT data available for advanced analytics. Here, ‘there is a spatial aspect’, fulfilled by the Notebook Server a ‘platform for spatial data scientists’. ArcPy offers tools for geospatial AI and a big data toolkit along with integration with R. One use case is satellite image analysis to spot pipeline encroachment (see also the WoodMac presentation below).

Adam Pittman reprised an ExxonMobil presentation made at the 2019 Esri plenary on the use of ArcGIS Indoors (AGI), Esri’s venture into BIM (building information management). A CAD model was imported into AGI and connect with operational data from safety systems, security (d-cameras), badging systems and HVAC. The 15 million square foot Exxon campus in The Woodlands has 23 miles of ‘walkable space’ hence the need for a wayfinding app. The Apple Bluetooth beacon system and ITS Systems indoor positioning also ran.

Jeff Allen presented on new developments in pipeline GIS. Here, a collaboration between Autodesk and ESRI is working to bridge the pipeline design/build gap. Moreover, while different tools are used to model upstream, midstream and downstream activity, ‘customers want only one’. Autocad/Civi3D/Revit data can blend with ArcGIS pipeline, combining linear referenced data with a network into a ‘seamless’ geodatabase from ‘wellhead to meter’. A demo showed a trace for min/max AOP design across a gas compression/pig station. A container concept, ‘GIS in GIS’ drills down inside pump station to show finer detail in the BIM model.

Gregor Calderwood presented on Tullow Oil’s use of Survey 123 during a seismic survey in Côte d’Ivoire. Survey 123 forms (created using the Borealis Excel template) record stakeholder engagement meetings and feed into the operations dashboard for reporting. A ‘grievance workflow’ captures complaints which are upload to the Borealis stakeholder engagement database. The system provides land access parcel mapping for affected landowners. The Côte d’Ivoire legal compensation formulas are programmed into Survey 123 forms. Tullow is now waiting to use UAVs for land marcel mapping and will be evaluating Drone2Map.

An Esri presentation on Tracker for ArcGIS showed how tablets, phones and smart watches can now feed into the Operations Dashboard for tracking activity in the field. Use cases include checking which well pads are visited and right-of-way patrolling. A ‘Quick Capture’ app is presented as an improvement on Survey 123 (‘too fiddly’) for aerial or walking pipeline control. Data can be captured into an on-site Esri spatio-temporal big data store or (real soon now) to the Esri Cloud. Analytics in ArcGIS is a ‘hot topic’. ArcGIS online offers some 25 analytics capabilities and ArcGIS Pro comes with 200+ pre-configured analytics tools. Many data scientists don’t know ESRI but are trying to do geospatial stuff, unaware of the Esri big data toolkit. Esri has decoupled ArcGIS binaries so they can run in the big data cloud and the Python ecosystem.

Stephen Bull presented a trial of AI/ML at WoodMac (now a Verisk unit). The idea is to automate the identification of well pads from satellite imagery using ESRI and open source technology, with help from sister company Geomni. WoodMac used ESA Sentinel 2 imagery and manual labelling with training in TensorFlow and Jupyter Lab. A single shot detector was trained with Coco (common object in context). The resulting model was deployed in ArcGIS Pro. 10m ESA S2 imagery, updated every few days, proved good for change detection on Texas well pads. In conclusion, good tagging is key and in general, ‘if you can see it you can train a model’. See also the Esri Sentinel-2 image services and the Deep dive into ML on ArcGis on youtube.

In the exploration-oriented session Galvin Tan and Jack Luo (both Shell) presented on GIS-enabling exploration in a UK license round. In June 2019, the UK opened a ‘mature areas’ round with a 120-day application period. Shell assembled a team of G&Gs, data manager and GIS specialist and set up a project using Shell’s ‘worldwide standard structure’. The project included data mining of corporate internal and regulator (OGA) sources, global 3rd party data providers, Shell’s past project archive and hard copy reports/books. Interpretations spanned geological models in ArcGIS (some on mylar/paper) and Shell’s cultural/surface data and ‘a lot of Shell PowerPoints’ from the geologists covering dry hole analysis and polygons of common risk segments. All of which was combined using ‘classic’ spatial analysis to produce a heat map of sweet spots, overlain with the blocks on offer. Next add infrastructure, pipelines, seismic cover, and non-technical risk (can we shoot seismics?). After the round and the award, the project data is cleaned-up and published into to corporate data sets for use by a wider audience and archival. The process in managed under a project assurance check list to capture metadata and context. Components of the data repository include Shell’s corporate data model, the EP Catalog and ‘maps’.

John Monkman (ExxonMobil) investigated the accuracy of spatial data. ExxonMobil is confident in its own acquired survey data but ‘most wells are not XOM drilled and surveyed’. What is the confidence of their location? A comparison of XOM data vs an unnamed 3rd party data vendor showed 450 wells with between 500m and 20km discrepancy. The main factors affecting accuracy are 1) a known coordinate reference system (CRS), 2) the accuracy of transformation to WGS84 (see for more on transform accuracy), 3) coordinate numerical precision, 4) survey equipment (today’s DGNSS can give sub meter accuracy, 5) when drilled/onshore-offshore. XOM uses a quality flag based on all of the above and a ‘traffic light’ system to indicate potential issues. In the future XOM plans to identify well spots from remote sensing imagery, and to data mine end of well reports to grab CRS/coordinates. XOM is also interested in large scale geographic conversion initiatives in collaboration with government or partners. Out of scope of the current work are altitude (Z), updated well surveys, time dependent/dynamic datums.

Bryan Yates (Orbital Insight) presented some possible uses of geospatial analytics. Orbital Insight’s GO platform claims the largest collection of satellite data available from multiple partners. Orbital collates multi-sensor data from satellites, smart phones, AIS and more, to allow remote intelligence gathering across areas of interest. One example was tracking Innergex’ progress on solar farm construction in Texas by watching workers’ foot traffic and evolving land use. Elsewhere, plant expansion and refinery outages can be spotted from Planet imagery. Foot traffic plus vehicle counts may signal the restart of a refinery. A ‘tip and queue’ service means that if something interesting is spotted, a satellite can be cued to look at the parking lot. An activity indicator for the Permian basin has shown a real slowdown (this in fall 2019!) with hotel foot traffic down and traffic at the Halliburton Field Complex at Odessa ‘all down since July 2019’. Global oil storage can be tracked by looking for floating top tanks, and then moving a radar sat in, or checking the shadow. Orbital Insight monitors 500 million barrels of storage for clients to spot build-ups, tracks gas station traffic in the US to monitor demand and counts cars in emerging markets (Rio, Egypt) for pollution and/or macroeconomic health. Supply chain monitoring for sustainable sourcing also ran ‘don’t buy stuff from non-sustainable areas in Brazil’. Chevron is a strategic investor.

Anuar Ospanov (NCOC) and Sam Bishop (Total) presented on the OGP Geomatics Committee’s new Offshore infrastructure survey data model (OISDM). The OISDM targets operations and maintenance of pipelines and platforms and supports ‘as built’ and ‘operating life’ survey comparison. The standard can capture side-scan sonar, ROVs, hi-res video and still imagery. OISDM was originally created for Chevron. 12 operators are now on board plus 6 survey companies. OISDM is based on the Esri geodatabase format. Tools of the OISDM trade include a geodatabase template, GML encoding and Enterprise Architect. A Rev C release is scheduled for Q2 2020 for use in inspect-repair-maintain surveys.

Tanya Knowles (UK Oil & Gas Authority) traced the UK Government’s push towards open data and the evolution of the UKCS as a ‘data-driven basin’. Previously, data release went through the joint industry CDA (Common data access) body which was expensive for newcomers. Today, ‘anyone can log in’ and access 173TB of data, 265k well logs, 12k well bores from the open data portal. OGA has also developed licensing round-specific portals. More from the OGA’s ArcGIS portal.

Oliver Morris traced the recent evolution of Neftex’ (a Halliburton unit) mapping technology. Neftex Insights (a service that provides regional geological interpretations) was previously delivered as ArcMap .mxd files. Generating these was labor intensive and the company lost staff in the downturn. A partnership with Safe Software and Esri saw the creation of an ArcGIS interoperability extension, based on Safe’s FME Cloud. This now allows Neftex to aggregate geological data across palinspastic maps and other data. Morris observed en passant that the Esri shapefile is still going strong after 30 years! Neftex also leverages the open source PostGIS system. A SQL query on PostGIS outputs to FME for delivery as file geodatabase, Zmap, Petrel, SHP and most recently, 3D PDF for VR. FME ships with over 5k coordinate transformations. More from QuickPlates from Neftex and also from Neftex associate PalaeoGIS.

Keith Fraley (40GEO) plans to turn IoT APIs into location-based intelligence. 40Geo’s Raptor Geo-IoT is an off-the-shelf solution for aggregating geospatial IoT feeds streaming them into enterprise GIS systems. Data comes from (inter alia) AIS vessel tracking and ADSB for aircraft.

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