Boris Chigarev ORCID 0000-0001-9903-2800 https://figshare.com/authors/Boris_Chigarev/6474086

Research Performance of Shell Scientific Publications During 2017-2019 Years. Bibliometric Analysis and Mapping

Start date of this research: 10 May 2019

Why Shell:

Royal Dutch Shell ...is one of the six oil and gas "supermajors" and the fifth-largest company in the world measured by 2018 revenues (and the largest based in Europe) https://en.wikipedia.org/wiki/Royal_Dutch_Shell

• Income for the period was $23.9 billion in 2018, compared with ​$13.4 billion in 2017. Earnings on a current cost of supplies basis increased to $24.4 billion, compared with $12.5 billion in 2017
• ...new projects, including the completion of an important chemical plant expansion in China and starting production from a deep-water development in the US Gulf of Mexico a year ahead of schedule. Overall, our production averaged 3.7 million barrels of oil equivalent a day in 2018, unchanged from 2017. STRATEGIC REPORT SHELL ANNUAL REPORT AND FORM 20-F 2018

Objectives: Mapping of bibliometric data of Shell petroleum company scientific publications during 2017-2019 years. Topic Mining and clustering.

Bibliometric and citation databases of scientific literature: OnePetro, Scopus, Web of Science

Used tools: VOSviewer - a software tool for constructing and visualizing bibliometric networks - http://www.vosviewer.com/ Bibliometrix - An R-tool for comprehensive science mapping analysis - http://www.bibliometrix.org/ Typora - a markdown editor - https://typora.io/ Notepad++ - a free source code editor - https://notepad-plus-plus.org/ SmoothCSV - a powerful CSV file editor - https://smoothcsv.com/2/

OnePetro

Queries to OnePetro: search for affiliation:"shell" has returned 7 446 results search for affiliation:("Shell"), published between 2014 and 2019 has returned 1 633 results - all search for affiliation:("Shell"), published between 2014 and 2019 has returned 1 404 results - conference papers search for affiliation:("Shell"), published between 2014 and 2019 has returned 121 results - articles search for affiliation:("Shell") in peer reviewed articles, published between 2014 and 2019 has returned 105 results

Remark:

• Conference papers is more concerned to business needs then articles
• We use OnePetro as starting point for our further research and building queries in Scopus and WoS
• 300 - 400 publications are sufficient for good bibliometric maps

So we use query: affiliation:("Shell"), published between 2017 and 2019 that has returned 566 results - conference papers

VOSviewer RIS files 21980 terms, 408 meet 10 min number of occorrence 245 - 60% used for further analysis.

Table 1 Top keywords (terms) occurrences in titles and abstracts of 245 conference papers, based on file OnePetro-KW-title-abstract-245.tsv.

Fig. 1 Terms map based on titles and abstracts of 245 conference papers, (file OnePetro-KW-title-abstract-245.png)

Remark

5 clusters: Project-Operation-Management; Model-Parameter-Uncertainty; Recovery-Effect-Injection; Monitoring-Presentation; Kuweit

Further we'll using 3 additional filters in our queries: Model, Project and Recovery.

Table 2 Top 20 terms by occurrence weight in cluster 1

Table 3 Top 20 terms by occurrence weight in cluster 2

Table 4 Top 20 terms by occurrence weight in cluster 3

Remark:

• The full list of terms by clusters are in file: OnePetro-KW-title-abstract-245-clusters.tsv
• The list was constructed from GML file exported from VOSviewer by using regex

Scopus

Queries to Scopus:

AFFILORG ( shell ) AND PUBYEAR > 2016 1,662 doc

• ( AFFILORG ( shell ) AND AFFILCOUNTRY ( russia ) ) AND PUBYEAR > 2016 0 docs
• ( AFFILORG ( shell ) AND AFFILCOUNTRY ( china ) ) AND PUBYEAR > 2016 73 docs
• ( AFFILORG ( shell ) AND AFFILCOUNTRY ( canada ) ) AND PUBYEAR > 2016 102 docs
• ( AFFILORG ( shell ) AND AFFILCOUNTRY ( "united states" ) ) AND PUBYEAR > 2016 795 docs
• ( AFFILORG ( shell ) AND TITLE-ABS-KEY ( model ) ) AND PUBYEAR > 2016 613 docs
• ( AFFILORG ( shell ) AND TITLE-ABS-KEY ( project* ) ) AND PUBYEAR > 2016 214 docs
• ( AFFILORG ( shell ) AND TITLE-ABS-KEY ( recovery ) ) AND PUBYEAR > 2016 171 docs

Remarks

There is no direct affiliations between Shell and Russian publications

Model, Project and Recovery are significant themes for Shell according Scopus (as well as OnePetro)

Table 5 The number of documents by type

Remark: Conference papers are more important for industry than articles

Table 6 The number of documents by subject areas

More in file: Scopus-1662-Analyze-Subject.csv

Table 7 The number of documents by authors affiliations

More in file: Scopus-1662-Analyze-Affiliation.csv

Table 8 The number of documents by funding sponsors

More in file: Scopus-1662-Analyze-FundingSponsor.csv

For more information see next files on Figshare:

• Scopus-1662-Analyze-Country.csv
• Scopus-1662-Analyze-Author.csv
• All scopus-Shell KW.tsv

Made by VOSviewer:

Fig. 2 Keywords co-occurrence for 1662 papers

Fig. 3 Keywords co-occurrence overlay for 1662 papers

Fig. 4 Co-authorship - countries for Shell papers in Scopus

Table 9 Shell papers citation - organizations (more in file: All scopus-Shell citation - organizations.tsv )

The keywords/terms from file: All scopus-Shell KW cooccurr GML.tsv (get from All scopus-Shell KW cooccurr GML.gml by using regex)

Table 10 Top 20 terms by occurrence weight in cluster 1

Table 11 Top 20 terms by occurrence weight in cluster 2

Table 12 Top 20 terms by occurrence weight in cluster 3

Table 13 Top 20 terms by occurrence weight in cluster 4

Table 14 Top 20 terms by occurrence weight in cluster 6

Remark: ALL number of clusters = 8, we present first 5 (see "All scopus-Shell KW cooccurr GML.tsv" for more data)

Bibliometric maps for: ( AFFILORG ( shell ) AND TITLE-ABS-KEY ( model ) ) AND PUBYEAR > 2016 613 docs

Fig. 5Keywords co-occurrence for 613 papers

Fig. 6 Keywords co-occurrence overlay for 613 papers

Fig. 7 Keywords co-occurrence overlay difference for 613 papers (top 20 keywords got from 1662 docs was removed from this map)

Fig. 8 Fragment from keywords co-occurrence overlay difference for 613 papers (Seismic prospecting and Velocity model and Velocity measurement)

Bibliometric maps for: ( AFFILORG ( shell ) AND TITLE-ABS-KEY ( project* ) ) AND PUBYEAR > 2016 214 docs

Fig. 9 Keywords co-occurrence for 214 papers

Fig. 10 Keywords co-occurrence overlay for 214 papers

Fig. 11 Keywords co-occurrence overlay difference for 214 papers (top 20 keywords got from 1662 docs was removed from this map)

Fig. 12 Keywords co-occurrence difference for 214 papers (top 20 keywords got from 1662 docs was removed from this map)

Bibliometric maps for: ( AFFILORG ( shell ) AND TITLE-ABS-KEY ( recovery ) ) AND PUBYEAR > 2016 171 docs

Fig. 13 Keywords co-occurrence for 171 papers

Fig. 14 Keywords co-occurrence overlay for 171 papers

Fig. 15 Keywords co-occurrence overlay difference for 171 papers (top 20 keywords got from 1662 docs was removed from this map)

Fig. 16 Keywords co-occurrence difference for 171 papers (top 20 keywords got from 1662 docs was removed from this map)

Fig. 17 Fragment from keywords co-occurrence overlay difference for 171 papers (enhanced recovery)

Some starting experiments with Bibliometrix (http://www.bibliometrix.org/)

Common remark: using the Bibliometrix package requires a separate study

Fig. 18 Wordcloud for: ( AFFILORG ( shell ) AND TITLE-ABS-KEY ( recovery ) ) AND PUBYEAR > 2016 171 docs; file: KeywordsPlus-171-docs.PNG

Fig. 19 Wordcloud for: ( AFFILORG ( shell ) AND TITLE-ABS-KEY ( project* ) ) AND PUBYEAR > 2016 216 docs; file: KeywordsPlus-216-docs.png (newer date then for 214 docs)

Fig. 20 Wordcloud for: ( AFFILORG ( shell ) AND TITLE-ABS-KEY ( model ) ) AND PUBYEAR > 2016 614 docs; file: KeywordsPlus-614-docs.PNG (newer date then for 613 docs)

Three Fields Plot: Visualize the main items of three fields (Keywords-KeywordsPlus-Affiliations), and how they are related through a Sankey diagram

Fig. 21 file: ( AFFILORG ( shell ) AND TITLE-ABS-KEY ( recovery ) ) AND PUBYEAR > 2016 171 docs; Three-Fields Plot Keywords-KeywordsPlus-Affiliations-171-docs.png

Fig. 22 ( AFFILORG ( shell ) AND TITLE-ABS-KEY ( project* ) ) AND PUBYEAR > 2016 216 docs; file: Three-Fields Plot Keywords-KeywordsPlus-Affiliations-216-docs.png (newer date then for 214 docs)

Fig. 23 ( AFFILORG ( shell ) AND TITLE-ABS-KEY ( model ) ) AND PUBYEAR > 2016 614 docs;file: Three-Fields Plot Keywords-KeywordsPlus-Affiliations-614-docs.png (newer date then for 613 docs)

Co-Word Analysis: The conceptual structure of a field, method: Multidimensional Scaling (MDS)

Fig. 24 ( AFFILORG ( shell ) AND TITLE-ABS-KEY ( recovery ) ) AND PUBYEAR > 2016 171 docs; file: Factorial Analysis MDS 171 docs.png

Fig. 25 ( AFFILORG ( shell ) AND TITLE-ABS-KEY ( project* ) ) AND PUBYEAR > 2016 216 docs; file: Factorial Analysis MDS 216 docs.png (newer date then for 214 docs)

Fig. 26 ( AFFILORG ( shell ) AND TITLE-ABS-KEY ( model ) ) AND PUBYEAR > 2016 614 docs; file: Factorial Analysis MDS 614 docs.png (newer date then for 613 docs)

Remark: for future research: data preparation and choice of parameters need more attentions to get informative figs

References:

Aria, M. & Cuccurullo, C. (2017) bibliometrix: An R-tool for comprehensive science mapping analysis, Journal of Informetrics, 11(4), pp 959-975, Elsevier.

Van Eck, N.J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523-538.

Boris Chigarev ORCID 0000-0001-9903-2800 https://figshare.com/authors/Boris_Chigarev/6474086 direct link: https://figshare.com/s/fce57c22704720db83b4