Demonstration of the importance of preprocessing the text fields of bibliometric records to identify promising research tasks: Case study of Scopus data on Petroleum Reservoir Engineering

Abstract. Background. Nowadays, bibliometric analysis of data from abstract databases is often used to identify relevant research tasks in order to rationalize the use of financial and other resources. Objective. To demonstrate the importance of preprocessing the text fields of bibliometric records to build a network of co-occurrence of terms and the possibility of subsequent use of Scimago Graphica for detailed study of different slices of clustering results in order to identify relevant research topics. Materials and methods. A total of 8,051 records exported from Scopus and matching the filter: (LIMIT-TO (EXACTKEYWORD, “Petroleum Reservoir Engineering”)) for the last ten years were used. VOSviewer and Scimago Graphica programs have been applied for bibliometric analysis. Results. The study showed the relevance of using the filter “LIMIT-TO EXACTKEYWORD” in the query to Scopus; the expediency of disclosing abbreviations in the text fields of records and preliminary clarification of texts; the effectiveness of using filters in the program Scimago Graphica to build a network of conjugation of terms in order to identify promising research topics. Conclusions. The promising research topics identified by the analysis can be described by the following terms: 1) nanopores, shale oil, pore size, molecular; 2) nanoparticles and nanofluids; 3) methane hydrate, hydrate saturation, hydrate bearing sediments. It is observed that in some cases, terms occurring in the same cluster are not the best choice for querying to expand the collection of publications on a given topic. Therefore, a separate study is proposed for this purpose using Apriori class algorithms.