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Article

Global Progress in Oil and Gas Well Research Using Bibliometric Analysis Based on VOSviewer and CiteSpace

by
Pan Zhang
1,2,
Yongjun Du
3,
Sijie Han
1,2 and
Qingan Qiu
4,*
1
Department of Industrial Engineering, School of Mechanical Engineering, Northwestern Polytechnical University, Xi’an 710072, China
2
Ministry of Industry and Information Technology Key Laboratory of Industrial Engineering and Intelligent Manufacturing, Northwestern Polytechnical University, Xi’an 710072, China
3
Department of Management Science and Engineering, School of Economics and Management, Lanzhou University of Technology, Lanzhou 730050, China
4
School of Management & Economics, Beijing Institute of Technology, Beijing 100081, China
*
Author to whom correspondence should be addressed.
Energies 2022, 15(15), 5447; https://doi.org/10.3390/en15155447
Submission received: 28 June 2022 / Revised: 21 July 2022 / Accepted: 23 July 2022 / Published: 27 July 2022
(This article belongs to the Special Issue Advances in Oil and Gas Well Engineering Science and Technology)
Browse Figures
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Abstract

:
Studies related to oil and gas wells have attracted worldwide interest due to the increasing energy shortfall and the requirement of sustainable development and environmental protection. However, the state of oil and gas wells in terms of research characteristics, technological megatrends, article-produced patterns, leading study items, hot topics, and frontiers is unclear. This work is aimed at filling the research gaps by performing a comprehensive bibliometric analysis of 6197 articles related to oil and gas wells published between 1900 and 2021. VOSviewer and CiteSpace software were used as the main data analysis and visualization tools. The analysis shows that the annual variation of article numbers, interdisciplinary numbers, and cumulative citations followed exponential growth. Oil and gas well research has promoted the expansion of research fields such as engineering, energy and fuels, geology, environmental sciences and ecology, materials science, and chemistry. The top 10 influential studies mainly focused on shale gas extraction and its impact on the environment. More studies were produced by larger author teams and inter-institution collaborations. Elkatatny and Guo have greatly contributed to the application of artificial intelligence in oil and gas wells. The two most contributing institutions were the Southwest Petr Univ and China Univ Petr from China. The People’s Republic of China, the US, and Canada were the countries with the most contributions to the development of oil and gas wells. The authoritative journal in engineering technology was J Petrol Sci Eng, in environment technology was Environ Sci Technol, in geology was Aapg Bull, and in materials was Cement Concrete Res. The keyword co-occurrence network cluster analysis indicated that oil well cement, new energy development, machine learning, hydraulic fracturing, and natural gas and oil wells are the predominant research topics. The research frontiers were oil extraction and its harmful components (1992–2016), oil and gas wells (1997–2016), porous media (2007–2016), and hydrogen and shale gas (2012–2021). This paper comprehensively and quantitatively analyzes all aspects of oil and gas well research for the first time and presents valuable information about active and authoritative research entities, cooperation patterns, technology trends, hotspots, and frontiers. Therefore, it can help governments, policymakers, related companies, and the scientific community understand the global progress in oil and gas well research and provide a reference for technology development and application.

1. Introduction

Petroleum and natural gas are the lifeblood of modern society development, and these underground resources are primarily extracted through drilling wells. The first oil well in the world was drilled by Edwin Drake in the middle of the wooded landscape of northwest Pennsylvania on 27 August 1859, indicating the birth of the modern petroleum industry [1]. The first natural gas well was drilled by William Hart in 1821 in Fredonia [2]. The world’s first complete natural gas industry system was first formed in the 1920s and 1930s in the United States. Therefore, oil and gas wells are essential research objects and material channels for human to extract underground oil and gas resources.
The invention of drilling well technology promotes oil and gas production and large-scale commercialization. With the wide application of petroleum and natural gas and the discovery of a large number of oil and gas fields around the world, many more wells have been created on Earth. Oil and gas well research mainly includes well drilling [3,4], cementing [5], completion [6,7], testing [8], logging and reservoir reconstruction technologies in conventional oil and gas, deep or deep-water oil and gas, and unconventional oil and gas wells [9]. In addition, in recent decades, technological progress, increasing energy shortfalls, and environmental impacts have driven research progress in oil and gas wells. This technological progress has resulted in the notable growth in terms of publication number concerning oil and gas production and application [10,11,12,13,14,15]. Many more articles have been published in oil and gas wells in recent decades under the background of the exponentially growing academic literature [16,17]. Facing the mushrooming of scientific literature in oil and gas well research, it is not easy for relative scholars to comprehensively understand and gain insight into the development state.
To resolve this problem, many scholars have adopted bibliometric methods to absorb the dynamic development in specific research fields [18,19]. The bibliometric analysis method has become a key tool for assessing and measuring science units by employing various software tools and digital databases [20,21]. Several review publications about the software tools available to perform bibliometric analyses [22,23,24,25] concluded that the most commonly used software tools are VOSviewer (freely available at http://www.vosviewer.com, accessed on 27 May 2022) [26], CiteSpace (https://citespace.podia.com/, accessed on 22 May 2022) [27], Gephi (https://gephi.org/, accessed on 22 May 2022) [28], Bibliometrix (https://www.bibliometrix.org/home/, accessed on 22 May 2022) [29], and SciMAT (https://sci2s.ugr.es/scimat/, accessed on 22 May 2022) [30]. In addition, bibliometric analysis was adopted to mine the development and progress of many research fields, including operations research and management science [31], information science and library science [32], solar energy [33], fuzzy research [34], blockchain research [35], and innovation [36,37,38] from micro, meso, or macro perspectives.
Some bibliometric studies related to oil and gas have been published in recent years. There were eight articles adopting a bibliometric analysis method to study the progress related to oil and gas, as shown in Table 1. However, there are some research gaps in the works displayed in Table 1. Most of the studies concentrated on quantifying some fields related to oil and gas, such as production, pipeline failure, environmental issues, and shale gas. However, essential oil and gas wells are lacking. Furthermore, few papers focused on analyzing the citation trends and interdisciplinary features. The evolution on hotspots and frontiers was not discussed through timeline visualization tools embedded in CiteSpace software.
Considering the above drawbacks, the main aims of this work were to resolve the following problems by analyzing the literature related to oil and gas wells published between 1900 and 2021 through theoretical methods and visualization tools:
RQ1: What are the output profiles and citation features of the literature in the field of oil and gas well research from 1900 to 2021?
RQ2: How can the most influenced papers be identified on the basis of the literature co-citation network?
RQ3: What are the interdisciplinary features of oil and gas well research published during 1900–2021?
RQ4: Which authors, institutions, countries, or journals have made great contributions to oil and gas well research, and what is the evolution of the cooperation patterns of study items?
RQ5: What are the hot topics and frontiers in oil and gas well research published between 1900 and 2021?
The structure of this article is as follows: Section 2 introduces the data collection process, analysis methods, and research content. In Section 3, we perform an analysis of the basic characteristics of the literature, including timeseries analysis of paper outputs, citation trends, etc. Section 4 presents the cooperation patterns and the leading authors, institutions, countries, and journals. The research hotspots and frontiers are discussed on the basis of author keywords in Section 5. The final section provides the conclusion and future study directions.

2. Data Source and Methods

2.1. Data

Figure 1 displays the data collection progress, analysis methods, and research content of this work. The data originated from the WOS core collection database (https://www-webofscience-com, accessed on 27 May 2022). WOS was chosen because this database covered more detailed paper information, more research fields and a longer timespan compared with other databases [47]. The literature data in the field of oil and gas wells can be retrieved from the WOS core collection database through a series of search terms and Boolean operations. The search strategy was TS = “oil and gas wells”, TS = “oil and gas well”, TS = “oil wells”, TS = “gas well”, TS = “oil well”, or TS = “gas wells”, where TS denotes the research topic in the WOS, and the double quotes can filter the whole noun phrases we focus on. The other conditions were as follows: indices, SCI, SSCI; span time, 1900–2021; research fields, more than 10 articles; languages, English; document types, articles. Finally, a total of 6197 full paper records were downloaded from the WOS core collection database as the research object of oil and gas well research.

2.2. Methods

To discuss the development progress, hot research topics, frontiers, and highly influential research entities, as well as cooperation patterns in the field of oil and gas well research within a certain time range, the following analysis methods and visualization tools were selected: (1) co-occurrence analysis: “co-occurrence” refers to the phenomenon that the information described by the feature items of the paper co-occurs; (2) timeline analysis: this method can present the progress trend in the research object in different study periods, which is helpful for scholars to gain insight into the progress characteristics at different stages; (3) burst detection analysis: this method can present keywords, authors, or citations that have received more attention in a short period of time to interpret their dynamic influence. From the perspective of keywords, keywords that gain more attention allow interpreting the research frontier to a certain extent.
The visualization tools adopted in this paper are shown in Figure 1. VOSviewer software (http://www.vosviewer.com, accessed on 27 May 2022) was utilized to build a co-occurrence network of the disciplines, study items, and the co-citation network of literature and journals. CiteSpace software (https://citespace.podia.com/, accessed on 22 May 2022) was utilized to generate a keyword cluster on the basis of the keyword co-occurrence network to exploit the hotspots of oil and gas well research. In addition, the hotspot timelines generated by CiteSpace implied the evolution of hotspots. Python programming language software was used to reveal the cooperation patterns between the studied items of published research. The most productive and influenced study items in oil and gas wells were discussed by their publication numbers and total citations.

3. Analysis of the Basic Characteristics of the Literature

3.1. Timeseries Analysis of Paper Outputs

Figure 2 presents the timeseries variations of publication outputs and logarithmic values in oil and gas well research indexed in the WOS core collection database from 1900 to 2021. From the picture, we can see that only a few articles related to oil and gas wells were indexed before 1962. There was a slight increase between 1962 and 1990. However, the indexed papers in the field of oil and gas wells have experienced explosive growth since 1990. The log linear distribution (blue) of indexed publication numbers in Figure 2 indicates that the annual publication numbers showed exponential growth from 1962 to 2021. Most of the papers (92.5% WOS paper) were published during 1992–2021. The exponential growth trend shows that studies related to oil and gas well have become a hotspot field in recent years with the increase in energy demand and the development of energy extraction technology.

3.2. Citation Trends

Figure 3 reflects the cumulative and annual number of citations attracted by literature in oil and gas wells from 1900 to 2021. As shown in Figure 3, the cumulative citations of oil and gas well research literature in the WOS core collection database grew exponentially, similar to publication number changes during 1900–2021. Apparently, there was a turning point for cumulative citations and annual citations in 1990. It was approximately 200 times that in 1990. However, it was more than 20,000 citations in 2002, 40,000 citations in 2010, 60,000 citations in 2014, and 80,000 citations in 2018. It is estimated to exceed 100,000 citations in 2022. There is no doubt that oil and gas well technology has attracted increasing attention from researchers worldwide. From the annual number of citations of oil and gas wells, we can conclude that the literature published between 2014 and 2016 had the most scientific influence.

3.3. Interdisciplinary Characters

Figure 4a presents the annual number variation of interdisciplinary papers and the corresponding proportion of oil and gas well research between 1900 and 2021. There is no doubt that the number of interdisciplinary papers in oil and gas well is consistent with the increasing pattern of the annual papers. However, the share of interdisciplinary papers fluctuated widely until 1990. Since 1990, it has stabilized with the increase in published articles. The share of interdisciplinary papers in oil and gas well research has remained at approximately 60% over the past decade, not increasing with the number of interdisciplinary papers.
Articles indexed by the WOS core collection have at least one WOS discipline, indicating the subject area covered by the paper. Figure 4b displays the disciplinary co-occurrence network map of oil and gas wells created by VOSviewer software. The node indicates the discipline in WOS. The node size indicates the discipline occurrence frequency. A larger node denotes a higher frequency. The links between the nodes indicate the co-occurrence status of two disciplines. If there is a connection between the nodes, it means that an article belongs to these two disciplines at the same time. In other words, this article has an interdisciplinary relationship. The thickness of the connection between each node indicates the strength of the interdisciplinary. A thicker connection denotes more significant interdisciplinarity. From the picture, we can see that the five disciplinary centers for interdisciplinary papers in the oil and gas fields were engineering, energy and fuels, environmental sciences and ecology, materials science, and geology.

3.4. Most Influential Literature

The literature co-citation network can identify the most influential research literature through citation frequency. The reference literature co-citation network can be mapped by VOSviewer software, as shown in Figure 5. Figure 5 presents the reference literature co-citation network of oil and gas well research published between 1900 and 2021 with a frequency of at least 20 times. It contains 195 nodes and 3617 edges. Each node represents a cited reference, and the node labels include author, publication year, journal and DOI. The node size indicates the cited frequency, and edges indicate that two papers are cited by an article. Apparently, the co-citation network was divided into five large cluster regions. Blue represents the papers related to the environment, green represents the papers concerning materials, purple represents the papers about energy and fuels, yellow represents the geology papers, and red represents the papers in engineering.
The top 10 most influential papers in oil and gas wells extracted from the reference co-citation network are summarized in Table 2 with the publishing year (PY), total citations (TC), corresponding author (CA), author numbers (AN), corresponding institution (CI), institution numbers (IN), corresponding country (CC) and country numbers (CN), first author (FA), and published journal (JI). The top 10 cited reference studies mainly focused on the impact of shale gas extraction and water sources (six articles). Shale gas extraction technology is a research hotspot as a new energy resource due to the shortage of traditional energy, such as oil and gas. Most of these landmark academic achievements were from the United States (nine articles).

4. Analysis of the Research Entities

4.1. Cooperation Patterns

In this section, we explore the cooperation patterns in oil and gas well research at the micro (authors), meso (institutions), and macro levels (countries/regions).

4.1.1. Cooperation Patterns of Authors

Figure 6 presents the author cooperation models in the field of oil and gas wells between 1990 and 2021. Figure 6a,b display the publication percentage and probability distribution produced by different author teams. Figure 6c presents the annual percentage changes in publications produced by different author teams. From Figure 6a, we observe that the papers in oil and gas well research written by the solo author only accounted for 6.75%, and the percentage declined over the entire period (shown in Figure 6c). Papers written by two to four authors had a similar evolution trend. However, papers performed by five and more authors accounted for 36.8%, and the proportion has steadily grown, exceeding 50% in 2021. The results of Figure 6 reveal that the majority of the literature was produced by author teams, and that more than half was produced by large-scale teams.

4.1.2. Cooperation Patterns of Institutions

Figure 7 presents the institutional cooperation patterns in the field of oil and gas wells. Figure 7a,b reflect the publication percentage and probability distribution produced by different institution teams. Figure 7c displays the annual percentage changes in publications produced by different institution teams. From Figure 7a, we can see that the proportion of within-institution collaboration was 48.02%, almost half. Percentage trends by year for different sizes of institutions are shown in Figure 7c. From the picture, we can see that there was a turning point between 2007 and 2008. The cooperation proportion within institutions showed a surprising decline, from 100% to 42%. Since 2008, intra-institutional cooperation and cooperation between two institutions have been the main cooperation modes at the institutional level in oil and gas well research.

4.1.3. Cooperation Patterns of Countries/Regions

Figure 8 presents the country collaboration patterns in oil and gas wells. Figure 8a,b displays the publication percentage and probability distribution produced by different country sizes. Figure 8c reflects the annual percentage changes in publications produced by different country sizes. From Figure 8a, we can observe that single-country/region publications in oil and gas well research accounted for approximately 80% of all publications. By analyzing the sizes of the country/region teams in Figure 8c, we can find that there has been no change in the mode of cooperation between countries in the field of oil and gas well research since 1992. Papers published by a single country have always dominated (approximately 80%).

4.2. Leading Research Entities

The results from Section 4.1 demonstrated that both author collaboration and institutional cooperation have shown prominent upward trends in oil and gas wells. Therefore, the output of study entities would be invalid if we counted each author, institution, and country/region listed in papers. In view of that, for the 6197 records in the field of oil and gas wells, we extracted study entities from the corresponding author address. Firstly, the contribution of the corresponding author to the work is second only to the first author, who is the original designer and mentor of the paper [48,49]. Secondly, they are usually senior and have a higher reputation in academia [48,50,51]. Lastly, they are the main contact person and person in charge of the work. The leading research entities were measured and assessed using total publications. More importantly, we also created the co-occurrence network of the study entities to identify the core entities.

4.2.1. Leading Authors

The author cooperation network can help us to identify the authors who made significant contributions to the development of oil and gas wells. Figure 9a presents the giant connected component of the author collaboration network with at least five papers created by VOSviewer. The nodes indicate authors, and the edges represent co-authorship relations between authors. It is worth noting that the node size is proportional to the author’s publication number, and the link width is proportional to the strength of collaborations. From the picture, we can see that the author cooperation network map presents the cooperation pattern of partial concentration and overall dispersion, and the network is grouped into 23 research communities, as illustrated by different colors in Figure 9a.
From the picture, we can see that the largest node was Elkatatny, who currently works at King Fahd University of Petroleum and Minerals. His research is mainly related to drilling fluid optimization, application of artificial intelligence, filter cake removal, machine learning, and oil-well cementing [52,53,54]. The second largest node was Guo from the University of Louisiana at Lafayette, whose community mainly focuses on shale-gas-related topics. Cheng, Guo, and Li are all from Southwest Petroleum University. The leading authors based on the cooperation network had some discrepancies compared to Figure 9b. Figure 9b presents the scientific influence of the top 10 corresponding authors extracted by publication numbers. The missing authors in Figure 9a (Plank and Frigaard) were independent groups that did not collaborate with other leader teams.

4.2.2. Leading Institutions

Figure 10a presents the giant connected component of the institution’s collaboration network in oil and gas wells research created by VOSviewer, in which each institution was filtered by a minimum of five publications in the field of oil and gas wells. This giant connected component consisted of 395 institutions and 1721 edges. The node size indicates the number of papers, and the edge thickness indicates the cooperation strength between institutions. By clustering embedded in VOSviewer, it was grouped into 21 clusters marked by different colors.
From Figure 10a, we can find that there are several clusters contributing to the development of the oil and gas wells research field. The cluster centered at the University of Pennsylvania was the largest, and the node color was red. It included 44 institutes, mainly from European and American countries. In this giant connected component, the top two most active nodes were Southwest Petr Univ and China Univ Petr, which are both from China, followed by Texas A&M Univ, China Univ Geosci, China Univ Petr East China, Univ Calgary, Univ Texas Austin, Chinese Acad Sci, King Fahd Univ Petr & Minerals, and Univ Alberta.
Figure 10b more deeply displays the scientific influence distribution of the top 10 corresponding institutes according to their citations. These were Southwest Petr Univ, China Univ Petr, China Univ Geosci, China Univ Petr East China, Texas A&M Univ, King Fahd Univ Petr & Minerals, Chinese Acad Sci, Univ Texas Austin, Univ Alberta, and Penn State Univ, respectively, which is consistent with the results in Figure 10a. Most of the active institutions in the field of oil and gas wells came from developed countries in Europe, the United States, and the main oil-producing countries.

4.2.3. Leading Countries/Regions

Similarly, the country/region collaboration network was also constructed by VOSviewer under the same conditions. The giant connected component of the country/region collaboration network consisted of 99 nodes and 531 links, as shown in Figure 11a. The picture we obtained shows a strong research collaboration among the USA, PR China, and Canada, which remained the core of the entire cooperation network. There is no doubt that China, Europe, and America were the most cooperative, with America having the core position in cooperation and paper numbers.
Figure 11b presents the scientific influence distribution of the top 10 corresponding countries. Geographically, there were four European and American countries, four Asian countries, one African country, and one South American country. From Figure 11b, we can see that the distribution of the academic influence at the country/region level did not have an obvious gap.

4.2.4. Leading Journals

The co-citation relationship between research journals can provide a glimpse into the co-occurrence pattern of authoritative journals and related knowledge and technology in the field of oil and gas well research. Figure 12a presents the giant connected component of the journal co-citation network in oil and gas wells research created through VOSviewer. The node size indicates their citations, and the link width represents the number of co-citations between each journal pair. The top ten largest nodes were J Petrol Sci Eng, Cement Concrete Res, Environ Sci Technol, Spe Ann Techn C Exh, J Nat Gas Sci Eng, J Petrol Technol, Constr Build Mater, Aapg Bull, Spe J, and P Natl Acad Sci. It clearly shows that the network was grouped into four communities through the cluster analysis embedded in VOSviewer. The red color marks the largest cluster, which had 114 journals, presenting the journal of engineering technology in oil and gas wells, and the most active node was J Petrol Sci Eng. Green implies journals concerning environmental technology, and Environ Sci Technol was the center journal. Yellow indicates geology, and Aapg Bull was the most active journal. Blue represents journals related to materials, and Cement Concrete Res was the authoritative journal.
Figure 12b shows the distribution of academic influences of the top 10 journals based on publication numbers. It clearly shows that most influence journals came from the red cluster and that there were no review journals. Average citations are a crucial index to assess the scientific influence of journals. SPE Reserv Eval Eng ranked first with the highest average citation. There is no doubt that high-impact journals identified on the basis of the journal co-occurrence network and according to the number of papers published were highly consistent.

5. Hotspots and Frontiers

5.1. Hotspots

The keywords of a paper can be used to generalize the main content of the paper, as well as describe and identify the research topics. Therefore, the keyword co-occurrence network was built and presented through CiteSpace software to explore the main hotspots in oil and gas well dating from 1992 to 2021. The parameters were set as follows: timespan, 1992 to 2021; time slice, 5 years; selection criteria, g-index (k = 25). Pathfinder was used to prune the network, and the visual form was cluster view—static. As shown in Figure 13, the final network contained 654 nodes and 1277 edges. As shown in Figure 13, we obtained 15 clusters through the LSI algorithm emended in CiteSpace. The modularity Q parameter was 0.6605, which is more than 0.5. The mean silhouette parameter value was 0.8282, which is more than 0.3.
From Figure 13, we can see that there were 17 clusters numbered #0 to #16. A smaller number indicates more keywords included in the cluster, and each cluster was made up of multiple closely related words. These were oil well cement, liquid loading, rheological properties, oil spill, mild steel, stress sensitivity, methane, geothermal energy, energy development, machine learning, hydraulic fracturing, natural gas, oil well, Gulf of Mexico, carbon dioxide, water, and Sichuan Basin.
The hotspot information of oil and gas well research obtained from Figure 13 is illustrated in Table 3 in detail, including hotspot size, mean silhouette value, hotspot name, top keywords, and noun phrases. As seen from Figure 13 and Table 2, the mainstream hot topics in oil and gas well research in the past 30 years could be roughly divided into several aspects. There is no doubt that oil and gas well drilling (hotspot #1, hotspot #12), cementing (hotspot #0), and testing (hotspot #3, hotspot #5, hotspot #6, hotspot #2, hotspot #14) technologies were still the largest hotspots. Then, a second hotspot was the application of new materials (hotspot #4) in oil and gas well engineering. Hotspot #7 was focused on the application and extraction of geothermal energy. The presentive keywords were geothermal energy, abandoned oil wells, direct heating, and thermal expansion annulus pressure. Hotspot #9 indicated the application of artificial intelligence in oil and gas well engineering. Hotspot #10 presented the new technology application of hydraulic fracturing in the extraction of oil and gas. Hotspot #13 and hotspot #16 were two locations, with potentially significant discoveries and development in oil and gas well engineering, which can be included in hotspot #8.
To more effectively summarize and to grasp the evolution process of research hotspots in oil and gas wells, the network map of keyword co-occurrence is further displayed in the form of a timeline to objectively reflect the trend of related hotspots from 1992 to 2021. The results are shown in Figure 14. The time slice was 5 years. The node size denotes the frequencies. The timepoint of the keyword indicates the year in which the keyword first appeared. The colors of nodes and links represent the different time slices. It is worth noting that, once a keyword appears for the first time, its position is fixed in the corresponding year. If the same keyword appears in subsequent years, it is not be repeated in the figure, but the cumulative frequency of subsequent occurrences is superimposed to the first occurrence of the keyword position in a different color. This is a good explanation for why the amount of literature collected in the initial years was very small, but many high-frequency keywords appeared in the figure.
Hot topics in the field of oil and gas well research have been constantly changing and restructuring. As early as 1992 and 1997, many hot research topics appeared, such as liquid loading, mild steel, machine learning, oil well, and natural gas, and the research interest has continued to this day. With the passage of time, some new research hotspots have also appeared in the subsequent time period, including the Sichuan Basin near 2010 and the Gulf of Mexico in 2005. There are also hotspots that have emerged in recent years, such as hydraulic fracturing in approximately 2016. On a whole, the connection density between the keywords in the figure was relatively high, and there was a strong relationship between the research topics. However, in recent years, the figure shows many small nodes clustered together, and the connection density was also high, but no large nodes were formed, which shows that, although there were many research results during this period, they were relatively scattered.

5.2. Frontiers

From Figure 14 in Section 5.1, we can intuitively explore how these hotspots evolved. In addition, the location of each keyword and phrase can help us explore cutting-edge research in each period in the field of oil and gas wells, as shown in Figure 15. As seen from Figure 15, the keyword co-occurrence network of each stage was very clear, but it was still difficult to clearly identify the frontier research in each stage. The frontier issues in the field of oil and gas wells can be reflected by keyword burst term detection. This can determine the keywords with a sudden increase in frequency in a certain period of time; these keywords reflect the frontier research and future research direction in this field to a certain extent.
In CiteSpace, the burst function can be used to detect the emergent words on the basis of the keyword co-occurrence clustering network and detect the emergent intensity of 30 keywords in total, as shown in Figure 16. The lifecycle of the emergent words can last for several years, before gradually diminishing and being replaced by new emergent words. In this way, the overall transition and transformation process of frontier topics in the field of oil and gas well research can be quickly understood. In Figure 16, the emergence words of oil and gas wells research in 1992–2021 are presented. We can see that the most important keyword was “oil well”, which appeared in 1997 with the highest burst strength of 27.14. Related research on oil wells has been the research frontier in the field of oil and gas wells research since 1997. The burst keywords that appeared in 1992 with high burst strength were polycyclic aromatic hydrocarbon (1992–2011), North Sea (1992–2011), hydrogen sulfide (1992–2016), petroleum (1992–2016), sediment (1992–2016), carbon dioxide (1992–2011), well (1992–2011), and environment (1992–2016), indicating that the research on oil extraction and its harmful components was the research frontier at that time. From 1997 to 2016, the study of oil and gas wells became a research center.
Porous media became a research frontier in 2007, and the related burst keywords were non-Darcy flow, flow, constraint, two-phase flow, and fluid loss additive. At the same time, developmental technologies of new energy resources have become a frontier field, mainly including hydrogen and shale gas.
Taking into account such a fact, too many countries around the world are facing a shortage of oil and gas. It is extremely important to find solutions that apply advanced exploration and exploitation technologies to generate enough oil and gas energy that is buried in deserts and oceans. In addition, finding ways to extract clean and new energy, such as shale gas and hydrogen energy, is equally crucial. Therefore, governments, policymakers, related companies and the scientific community should familiarize themselves with the broad knowledge in oil and gas wells research to promote the generation of energy. For this reason, we carried out a comprehensive bibliometric analysis of 6197 articles related to oil and gas wells research published from 1900 to 2021. The knowledge maps in this paper were drawn by CiteSpace and VOSviewer software. Doing so could reveal the current and future research trends in oil and gas wells.
The exponential growth trend of article numbers and their cumulative citations have witnessed widespread attention around the world in oil and gas well research. Articles published in 2016 in oil and gas wells received widespread attention, which can be observed by their citations. Interdisciplinary articles related to oil and gas wells have increased exponentially, and the core subjects were engineering, energy and fuels, geology, environmental sciences and ecology, and materials science. The top 10 cited reference studies mainly focused on shale gas extraction and its impact on the environment. In oil and gas well research, more studies were produced by larger author teams and inter-institution collaboration. Elkatatny and Guo have greatly contributed to the research of drilling fluid optimization, application of artificial intelligence and machine learning, oil-well cementing, and the extraction effect of shale gas. The two most contributing institutions were the Southwest Petr Univ and China Univ Petr from China. China, the United States, and Canada were the top three countries that contributing to the progress in oil and gas well. The authoritative journal in engineering technology was J Petrol Sci Eng, in environment technology was Environ Sci Technol, in geology was Aapg Bull, and in materials was Cement Concrete Res. The research hotspots of oil and gas wells research focused on oil well cement, energy development, machine learning, hydraulic fracturing, natural gas, and oil well. The research frontiers were oil extraction and its harmful components (1992–2016), oil and gas wells (1997–2016), porous media (2007–2016), and hydrogen and shale gas (2012–2021).
According to the frontier analysis in oil and gas wells, we can find that the application of artificial intelligence and the exploration and exploitation methods of new energy, such as shale gas and hydrogen energy, will be important for future research. Artificial intelligence techniques have been applied to all aspects of oil and gas extraction, and the main research directions include crude oil intelligent exploration, intelligent drilling, and smart oil fields. Future research directions related to shale gas will mainly focus on ways to reduce the impact on the environment and high-precision intelligent fracturing.

Author Contributions

Conceptualization, P.Z., S.H. and Y.D.; methodology and formal analysis, P.Z. and S.H.; software, P.Z. and S.H.; data curation, P.Z.; writing—original draft preparation, P.Z. and Y.D.; writing—review and editing, Q.Q.; project administration, Q.Q.; funding acquisition, Y.D. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Natural Science Foundation of China (Nos. 72161025, 71871181, and 71631001) and the Featured Liberal Arts Development Plan of NPU (2021TSWK0015).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data used in this paper are all publicly accessible. The paper data in oil and gas well research can be downloaded via https://www-webofscience-com.libproxy1.nus.edu.sg/wos/woscc/basic-searchs, accessed on 27 May 2022.

Acknowledgments

We would like to thank all contributors who supported the field work and the data collection and analysis.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Data collection progress, analysis methods, and research content.
Figure 1. Data collection progress, analysis methods, and research content.
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Figure 2. Timeseries variations of publication outputs and logarithmic value changes in oil and gas well research in the WOS core collection database, 1900–2021.
Figure 2. Timeseries variations of publication outputs and logarithmic value changes in oil and gas well research in the WOS core collection database, 1900–2021.
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Figure 3. Cumulative and annual number of citations attracted by literature in oil and gas wells from 1900 to 2021.
Figure 3. Cumulative and annual number of citations attracted by literature in oil and gas wells from 1900 to 2021.
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Figure 4. (a) Annual number variation of interdisciplinary papers and corresponding proportion between 1900 and 2021. (b) Disciplinary co-occurrence network in the field of oil and gas well research.
Figure 4. (a) Annual number variation of interdisciplinary papers and corresponding proportion between 1900 and 2021. (b) Disciplinary co-occurrence network in the field of oil and gas well research.
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Figure 5. Literature co-citation network of oil and gas well research published between 1900 and 2021.
Figure 5. Literature co-citation network of oil and gas well research published between 1900 and 2021.
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Figure 6. The author cooperation models in oil and gas wells. (a,b) The publication percentage and probability distribution produced by different author teams. (c) Annual percentage changes in publications produced by different author teams.
Figure 6. The author cooperation models in oil and gas wells. (a,b) The publication percentage and probability distribution produced by different author teams. (c) Annual percentage changes in publications produced by different author teams.
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Figure 7. Institutional cooperation models in oil and gas wells. (a,b) The publication percentage and probability distribution produced by different institution teams. (c) Annual percentage changes in publications produced by different institution teams.
Figure 7. Institutional cooperation models in oil and gas wells. (a,b) The publication percentage and probability distribution produced by different institution teams. (c) Annual percentage changes in publications produced by different institution teams.
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Figure 8. The country collaboration patterns in oil and gas wells. (a,b) The publication percentage and probability distribution produced by different country sizes. (c) Annual percentage changes in publications produced by different country sizes.
Figure 8. The country collaboration patterns in oil and gas wells. (a,b) The publication percentage and probability distribution produced by different country sizes. (c) Annual percentage changes in publications produced by different country sizes.
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Figure 9. (a) The giant connected component of author collaboration network with at least five papers generated by VOSviewer. (b) Top 10 most scientific influence corresponding authors. The asterisk in figure indicates the outliers.
Figure 9. (a) The giant connected component of author collaboration network with at least five papers generated by VOSviewer. (b) Top 10 most scientific influence corresponding authors. The asterisk in figure indicates the outliers.
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Figure 10. (a) The giant connected component of the institutional collaboration network with at least five papers generated by VOSviewer. (b) The top 10 most scientific influence corresponding institutions. The asterisk in figure indicates the outliers.
Figure 10. (a) The giant connected component of the institutional collaboration network with at least five papers generated by VOSviewer. (b) The top 10 most scientific influence corresponding institutions. The asterisk in figure indicates the outliers.
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Figure 11. (a) The giant connected component of country/region collaboration network generated by VOSviewer. (b) Top 10 most scientific influence corresponding country/region. The asterisk in figure indicates the outliers.
Figure 11. (a) The giant connected component of country/region collaboration network generated by VOSviewer. (b) Top 10 most scientific influence corresponding country/region. The asterisk in figure indicates the outliers.
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Figure 12. (a) The giant connected component of journal co-citation network of oil and gas wells research between 1992 and 2021 generated by VOSviewer. (b) Top 10 most scientific influence journals. The asterisk in figure indicates the outliers.
Figure 12. (a) The giant connected component of journal co-citation network of oil and gas wells research between 1992 and 2021 generated by VOSviewer. (b) Top 10 most scientific influence journals. The asterisk in figure indicates the outliers.
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Figure 13. Seventeen clusters of keyword co-occurrence networks in the field of oil and gas wells generated by CiteSpace, 1992–2021.
Figure 13. Seventeen clusters of keyword co-occurrence networks in the field of oil and gas wells generated by CiteSpace, 1992–2021.
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Figure 14. A timeline visualization of the 17 hotspots in the field of oil and gas wells, 1992–2021.
Figure 14. A timeline visualization of the 17 hotspots in the field of oil and gas wells, 1992–2021.
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Figure 15. Mapping of the changes of frontiers in oil and gas wells research in different periods.
Figure 15. Mapping of the changes of frontiers in oil and gas wells research in different periods.
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Figure 16. The emergence words in oil and gas wells research in 1992–2021.
Figure 16. The emergence words in oil and gas wells research in 1992–2021.
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Table
Table 1. Bibliometric studies in oil and gas well research.
Table 1. Bibliometric studies in oil and gas well research.
Ref.TitleYearContributions
[39]A bibliometric analysis on oil and gas pipeline failure consequence analysis2021Evaluating research patterns in oil and gas pipeline failure consequences considering 20 years of scientific documents.
[40]New research trends in unconventional oil and gas environmental issue: a bibliometric analysis2020A bibliometrics overview of unconventional oil and gas environmental issue from 1990 to 2018.
[41]A bibliometric analysis of sustainable oil and gas production research using VOSviewer2022Using VOSviewer software to carry out a bibliometric analysis of research on sustainable oil and gas production from 1994 to 2021.
[42]How marketized is China’s natural gas industry? A bibliometric analysis2021Quantitative analysis of the marketization degree of China’s natural gas industry through a literature analysis.
[43]Safety and security of oil and gas pipeline transportation: a systematic analysis of research trends and future needs using WoS2021Quantitating the security and safety of oil and gas pipeline transportation through informetric analysis.
[44]Alternative marine fuel research advances and future trends: a bibliometric knowledge mapping approach2022Quantifying research of the alternative marine fuel.
[45]Bibliometric analysis; characteristics and trends of refuse derived fuel research2022Carrying out a bibliometric analysis for refuse-derived fuel research.
[46]Global research trends on shale gas from 2010–2020 using a bibliometric approach2022Quantifying the global research in the field of shale gas published between 2010 and 2020 through the bibliometric method.
Table
Table 2. Most influenced papers extracted from the literature co-citation network.
Table 2. Most influenced papers extracted from the literature co-citation network.
PYTC (WOS)Cited FrequencyTitleResearch AreaJICA/FA (AN)CI (AI)CC (CN)
2013943109Impact of shale gas development on regional water qualityScience and technology—other topicsScienceVidic, R. D. (5)Univ Pittsburgh (2)USA (1)
2002910106A critical review of the risks to water resources from unconventional shale gas development and hydraulic fracturing in the United StatesEngineering; environmental sciences and ecologyEnviron. Sci. Technol.Vengosh, Avner (5)Duke Univ (4)USA (1)
2011830105Methane contamination of drinking water accompanying gas-well drilling and hydraulic fracturingScience and technology—other topicsProc. Natl. Acad. Sci.Osborn, SG/Jackson, RB (4)Duke Univ (1)USA (1)
196917284Analysis and prediction of minimum flow rate for continuous removal of liquids from gas wellsEnergy and fuels, engineering, and geologyJ. Pet. Technol.TURNER, RG (3)//
201421982Oil and gas wells and their integrity: implications for shale and unconventional resource exploitationGeologyMar. Pet. Geol.Davies, Richard J. (9)Univ Durham (5)England (2)
201235881Geochemical evidence for possible natural migration of Marcellus Formation brine to shallow aquifers in PennsylvaniaScience and technology—other topicsProc. Natl. Acad. Sci.Warner, NR/Vengosh, A (8)Duke Univ (2)USA (1)
194542177Analysis of decline curvesEngineering, metallurgy, and metallurgical engineering/ARPS, JJ (1)//
201334774Geochemical evaluation of flowback brine from Marcellus gas wells in Pennsylvania, USAGeochemistry and geophysicsAppl. Geochem.Haluszczak, Lara O./Rose, Arthur W.Penn State Univ (1)USA (1)
201337069Increased stray gas abundance in a subset of drinking water wells near Marcellus shale gas extractionScience and technology—other topicsProc. Natl. Acad. Sci.Jackson, RB (9)Duke Univ (3)USA (1)
201157260Water management challenges associated with the production of shale gas by hydraulic fracturingGeochemistry and geophysics, and mineralogyElementsGregory, Kelvin B. (3)Carnegie Mellon Univ (2)USA (1)
Table
Table 3. Hotspot information statistics in the field of oil and gas wells research.
Table 3. Hotspot information statistics in the field of oil and gas wells research.
Hotspots IDSizeSilhouetteHotspot NameTop Terms (LSI)
0610.849Oil well cementOil well cement; cement paste; uniaxial compression; gel transition time; shale gas|mechanical properties; oil-well cement; shallow wells; gel transition time; shale gas
1480.888Liquid loadingtwo-phase flow; vertical wellbore; transient simulation; Duong’s method; hybrid method|sensitivity analysis; Monte Carlo simulation; wellbore temperature; high-temperature formation; Longmaxi
2460.804Rheological propertiesPorous media; energy balance; temperature transient; fracturing fluid; hollow perlite microspheres|drilling fluid; soaking time; deep mudstone; clay-bearing reservoir; carbonation resistance
3450.786Oil spillHydraulic fracturing; ribosomal RNA gene analysis; low biomass samples; area; organic compound|polycyclic aromatic hydrocarbons; carbon isotope ratios; total petrol; hydrocarbon; characteristic auxiliaries; foaming agent series
4450.782Mild steelCarbon steel; corrosion inhibitors; nonionic surfactants; formation water; acid inhibition|corrosion inhibitor; impedance spectroscopy; PKA analysis; DLC coatings; salt-affected soils
5430.781Stress sensitivityStress sensitivity; production performance; carbonate gas reservoirs; composite reservoirs; ultimate recovery|ultimate recovery; production forecast; unconventional gas; parameter determination; production analysis
6420.782MethaneHydraulic fracturing; water quality; isotope tracers; critical flow rate; tight sandstone gas|natural gas; emission; soil; RN 222; flowback fluids
7400.813Geothermal energyGeothermal energy; abandoned oil wells; direct heating; organic Rankine cycle; thermal expansion annulus pressure; working fluids|hydrothermal enhanced geothermal system; enhanced geothermal system; shallow depth; hydrothermal system
8400.859Energy developmentEnergy development; grassland songbirds; anthropogenic noise; edge effects; nesting success|gas development; forest fragmentation; biotic homogenization; Allegheny national forest; forest songbirds
9390.811Machine learningHydraulic fracturing; multiple fracture growth; fluid viscosity; rate transient analysis; multistage hydraulic fracturing|machine learning; deep learning; production forecasting; phase flow; two-fluid model
10390.886Hydraulic fracturingHydraulic fracturing; water quality; isotope tracers; coprecipitation; flowback fluids|Marcellus shale; coprecipitation; flowback fluids; risk assessment; greenhouse gases
11380.802Natural gasNatural gas; United States; abandoned oil; Williston Basin; North Dakota|horizontal well; transient analysis; performance; media; gas flow
12320.83Oil wellHeat transfer; flow; system; methane; model|performance; permeability; fracture; film flow; Sichuan Basin
13280.84Gulf of Mexicocement sheath; finite element; graphene oxide; wellbore irregularity; sensitivity analysis|wellbore integrity; finite elements; hydraulic tong; stress concentration; water hammer effect
14240.831Carbon dioxideNumerical simulation; temperature field; fragment mechanism; stress distribution; laser perforation|hydraulic fracturing; example calculation; atmospheric models; bile metabolites; CO2 fracturing
15150.922WaterReservoir; porous media; recovery; swelling clay; sandstone|water; flow; permeability; thermodynamic property; Posidonia shale
16140.954Sichuan BasinLongmaxi Formation; Wufeng Formation; Yangtze Plate; differential enrichment; confining pressure|Barnett shale; Silurian Longmaxi; miniature core plug; gold-tube pyrolysis; residual TOC content
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Zhang, P.; Du, Y.; Han, S.; Qiu, Q. Global Progress in Oil and Gas Well Research Using Bibliometric Analysis Based on VOSviewer and CiteSpace. Energies 2022, 15, 5447. https://doi.org/10.3390/en15155447

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Zhang P, Du Y, Han S, Qiu Q. Global Progress in Oil and Gas Well Research Using Bibliometric Analysis Based on VOSviewer and CiteSpace. Energies. 2022; 15(15):5447. https://doi.org/10.3390/en15155447

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Zhang, Pan, Yongjun Du, Sijie Han, and Qingan Qiu. 2022. "Global Progress in Oil and Gas Well Research Using Bibliometric Analysis Based on VOSviewer and CiteSpace" Energies 15, no. 15: 5447. https://doi.org/10.3390/en15155447

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