PROCESSING, ANALYSIS, AND DISTRIBUTION OF SHALE DATA OVER GIS SERVICES AND WEB APPS

Transcription

1 PROCESSING, ANALYSIS, AND DISTRIBUTION OF SHALE DATA OVER GIS SERVICES AND WEB APPS Roman Boros, Peter Pavlicko 2018 ESRI Petroleum User Conference Houston, May 10, 2018

2 Abstract Production of oil and gas from shale and tight formations in North America has transformed the global energy landscape in many ways. Having easy access to the most up-to-date map data about the shale plays is critical for successful development decisions. This paper will present how Rystad Energy has succeeded to streamline the process from data updates, through service synchronization in a cloud to distribution and visualization in a web app. All deployment is based on ESRI technology, such as ArcGIS Pro, Data Interoperability extension, ArcGIS Online, REST services and Web App Builder.

3 Objective Brief introduction to Rystad Energy Importance of spatial data and maps in company s business Map data sources, processing, outputs/products Use case scenario of deploying and using ArcGIS technology Processing of source data from various sources Analysis and modelling Transition from Shapefiles to Services Shale data outputs delivery Developing an Online GIS platform Share/exchange experiences

4 Initial aspects of new GIS business development model Use Case North America Shale Data Processing and modeling Transforming and joining non-spatial and spatial data Developing Online GIS Platform Conclusion Remarks

5 Rystad Energy Business Importance of spatial data Growing Data Volumes and Demands from clients Rystad Energy is an independent energy research and business intelligence company providing data, tools, analytics and consultancy services to clients exposed to the energy industry across the globe. Maps and GIS is not a core business, but provide supportive function in tools, analyses, projects and products. Mapping includes upstream petroleum spatial data on global level: wells, fields, discoveries, license blocks, geology, seismic, etc. Data is collected and updated from various formats, various data providers, mostly from public sources. Spatial data serve different types of outputs: Analyses and reports Map viewer in Cube browser Ucube, NASWellCube, Dcube, etc. main products Internal processing and computing GIS deliveries for end clients (static formats, usually Shapefiles) Requirements from clients (internal users as well): Online access to data, always up-to-date

6 Rethinking the Strategy Data From Various Sources And Shapefiles Shapefiles the starting point How to deliver maps to clients (not in Shapefiles anymore)? How to set up an effective updating process? (online updates) and use GIS resources we ve had before and minimize developers resources and side-effect: improvement of organizational data not ShapeFiles anymore

7 The Strategy Online Data Updating And Delivery Mechanisms Cloud environment Hosted Clients GIS services ArcGIS REST, WMS, WFS HTTPS auth. GIS Services (end-users) RE GIS production environment regular updates HTTPS auth. Web map Apps (end-users) External data GIS Tools Web App Builder (Dev. Ed.) RE GeoDatabase Data Processing Analysis RE Databases Other products NAS WELL Cube XY Cube Projects Reports Spatial database Core business databases

8 Initial aspects of new GIS business development model Use Case North America Shale Data Processing and modeling Transforming and joining non-spatial and spatial data Developing Online GIS Platform Conclusion Remarks

9 North America Shale Use Case Specific Use case Production of oil and gas from shale and tight formations from North America has transformed the global energy landscape Reflected in our business, demand for detailed well level, geology and acreage data Growing number of products North America Shale Solutions: NASWELLCUBE SHALE UPSTREAM ANALYTICS SHALE INTEL Rystad Energy office in Houston US Shale: total production from horizontal wells by play in Thousand boe/d Caney Shale, US Tuscaloosa Marine Shale, US Springer Shale, US Greater Green River Tight, US Meramec Shale, US Uinta-Piceance Tight Oil_Utah, US Buda, US Woodbine/Eaglebine Shale, US Hunton Lime, US Oklahoma (Other), US PRB Tight Oil, US Cotton Valley, US Mississippian Lime, US Utica Shale, US Anadarko Tight Oil, US Niobrara Shale, US Granite Wash, US Permian Midland Tight, US Woodford Shale, US Permian Delaware Tight, US Fayetteville Shale, US Haynesville/Bossier Shale, US Bakken Shale, US Barnett Shale, US Eagle Ford Shale, US Marcellus Shale, US

10 NASWellcube From raw data to cube browser North American Shale Well Database (NASWellCube) Complex tool that provides an in-depth insight into North American shale and conventional well activities. Database accessible in cube browser (CB) Desktop application with table, chart and map viewer CB map viewer used to displays well data as point layer on top of background map layer stored in Shapefile format on client Continuous requests lead to recent development of map viewer based on online map services

11 Initial aspects of new GIS business development model Use Case North America Shale Data Processing and modeling Transforming and joining non-spatial and spatial data Developing Online GIS Platform Conclusion Remarks

12 Shale - Data Access and Analysis Data Factory From Raw, Inconsistent Data to A Uniform, Accurate Cube Format 1 Raw data collection 5 GeoDatabase 2 Data Cleaning 3 Data analysis Forecast Forecasting Economics Chemicals 0 PXD EOG XEC OXY MEW 0 NASWellCube Reports Water

13 GIS analyses used for shale acreage prospectivity 1. Initial geo-processing: Raster layer input data as a result of surface interpolation of digitalized point vector data for several key parameters. 2. Reclassification: Reclassified raster layers representing the score categories defined for each input raster dataset. Score range from 5 (for the best value intervals of the input parameters) to 1 (or zero) for least suitable areas. Depth intervals (feet): 0 to 1,000 OR > 15,000 score 1 1,000 to 3,000 OR 12,000 to 15,000 score 2 3,000 to 4,000 OR 8,000 to 12,000 score 3 4,000 to 5,000 OR 7,000 to 8,000 score 4 5,000 to 7,000 score 5 Thickness intervals (feet): 0 to 100 score to 200 score to 400 score to 500 score 4 > 500 score 5 Vitrinite Reflectance intervals (Ro): 0.0 to 0.6 OR > 2.0 score to 0.7 OR 1.9 to 2.0 score to 0.8 OR 1.4 to 1.9 score to 1.1 OR 1.3 to 1.4 score to 1.3 score 5 3. Map algebra: Prospectivity raster map as a result of weighted combination of reclassified score raster datasets. Raster calculator: Prospectivity [valuation_raster] = = if ([Ro_score] > 0) true: 0.33*[Depth_score]+0.33*[Thickness_score]+0.34*[Ro_score] false: 0

14 BlueStone Nat. Res. Devon Energy EnerVest/EVEP JV EOG Resources ExxonMobil Titan Energy Total Trinity River Energy GIS analyses Additional Analysis - Relative comparision of company portfolios Percentage of company acreage by prospectivity score 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% Barnett Shale 0% Prospectivity: Valuation: High Low

15 Initial aspects of new GIS business development model Use Case North America Shale Data Processing and modeling Transforming and joining non-spatial and spatial data Developing Online GIS Platform Conclusion Remarks

16 Data Transformation FME - Effective Tools for Processing and Updating Data in Online Environment Various source data processing greatly reduce work and support automation Data validation process testing and repairing non-valid data Incremental updates (changes only) impact on online services Time-scheduling updates (Python/Windows Task Scheduling)

17 Data Transformation Transforming Non-Spatial to Spatial FME Workbench useful geometry constructors Vertex Creator, LineCreation Unique ID connection between spatial and non/spatial data

18 Spatial Data Visualization Models Outputs

19 Initial aspects of new GIS business development model Use Case North America Shale Data Processing and modeling Transforming and joining non-spatial and spatial data Developing Online GIS Platform Conclusion Remarks

20 Online GIS Outputs GIS Web Maps and Services GIS Web Map Applications GIS Services Online interactive map applications using Web browser (desktop or mobile devices) Search, analyze and export spatial data and map layouts (e.g. PDF) Predefined map views and analytical tools (filters, selection tools) Add your own data or map services (Shapefiles, KML, WMS, etc.) Non-visual interface for maps and spatial data More advanced analytical capabilities using your own GIS software Create your own applications using REST API and other communication protocols (WMS, WFS)

21 GIS Services Running in Cloud Hosted GIS services, running in cloud-based environment Availability 24/7, anywhere with Internet connection Cost factors (HW and SW infrastructure, operational costs) Online data updating process, always up-to-date version of data Alternative way to distribute spatial-related data from all databases NORTH AMERICA SHALE SOLUTIONS UPSTREAM SOLUTIONS

22 GIS Services Advantaged From User Perspective Use advantages of your own GIS products (e.g. ArcGIS Desktop, QGIS) Online data communication (user/password) No imports More advanced options for data analyses and outputs than Web Map applications Download and store data in your GIS database Supported GIS services protocols: ArcGIS REST (JSON) Web Map Service (WMS 1.3.0) Web Feature Service (WFS 2.0.0) Cloud environment Connect to service Analyze online data Analytical layouts or outputs GIS services Download data

23 Developing Online maps and Services Role of ArcGIS Online, Web Application Builder ArcGIS Online as a gallery of all maps and services (search, metadata...) web maps (needed for custom applications) Web Application Builder developer edition (widgets customization)

24 GIS Web Map Applications Application Layout basemaps filters add own data previous/forward map view measure search drawing export/print map legend layers map views Interactive content coordinates table/attribute data

25 Initial aspects of new GIS business development model Use Case North America Shale Data Processing and modeling Transforming and joining non-spatial and spatial data Developing Online GIS Platform Conclusion Remarks

26 Experiences to Share Current Technology Limitations Web Maps/Web Application Builder: Organizing layers in TOC Groups are not supported (only flat structure) Tile Layers always on bottom disadvantage when combining tile/dynamic layers Scale-dependent visualization of map layers Missing possibility to apply several styles on a layer depending on scale Duplicates number of layers in TOC (impact also on applications performance) ArcGIS Online Great for internal organization usage Limited options for developing custom business model based on AGOL (Terms of Use) Make Named users accounts available to thirdparties?

27 Conclusion ArcGIS Platform User s Perspective ArcGIS is a flexible and user-oriented platform for developing custom GIS business - several challenging issues to implement to make life easier for end-users Scale drives everything Thank you!