Purpose Websites, search engines, recommender systems, artificial intelligence and digital libraries have the potential to support serendipity for unexpected interaction with information and ideas which would lead to favored information discoveries. This paper aims to explore the current state of research into serendipity particularly related to information encountering. Design/methodology/approach This study provides bibliometric review of 166 studies on serendipity extracted from the Web of Science. Two bibliometric analysis tools HisCite and RStudio (Biblioshiny) are used on 30 years of data. Citation counts and bibliographic records of the papers are assessed using HisCite. Moreover, visualization of prominent sources, countries, keywords and the collaborative networks of authors and institutions are assessed using RStudio (Biblioshiny) software. A total of 166 papers on serendipity were found from the period 1989 to 2022, and the most influential authors, articles, journals, institutions and countries among these were determined. Findings The highest numbers of 11 papers were published in the year 2019. Makri and Erdelez are the most influential authors for contributing studies on serendipity. “Journal of Documentation” is the top-ranking journal. University College London is the prominent affiliation contributing highest number of studies on serendipity. The UK and the USA are the prominent nations contributing highest number of research. Authorship pattern for research on serendipity reveals involvement of single author in majority of the studies. OA Green model is the most preferred model for archiving of research articles by the authors who worked on serendipity. In addition, majority of the research outputs have received a citation ranging from 0 to 50. Originality/value To the best of the authors’ knowledge, this paper may be the first bibliometric analysis on serendipity research using bibliometric tools in library and information science studies. The paper would definitely open new avenues for other serendipity researchers.

The Complex pore geometry of carbonate rocks pose challenges in the formation evaluation, production planning and reservoir simulation. Various diagenetic processes, including solution activities causes lateral and vertical heterogeneities in the formation. There exist two main pore networks in the carbonates which controls the petrophysical and productive characteristics, such as, the interparticle pore network (mainly matrix porosity) and secondary pore network (comprising of vuggy pores as well as fractures). The Minagish Oolite reservoir under this current study is no different and hence warrants a clear understanding of the heterogeneity in the reservoir in order to plan a better completion strategy. In view of this, a study was carried out in one of the wells integrating conventional well log data, Images logs, NMR logs, Sonic logs, Pressure tests and Core to decide right interval to perforate out of the available zones of interests. Conventional logs are unable to address the geological complexity posed by the reservoir. The different textural elements coexisting in the reservoir (the different pore sizes and their distribution) is identified and captured from image logs and NMR. Integration of NMR and borehole image data allowed us to partition the porosity according to pore sizes and compute continuous permeability which was then calibrated to the mobility obtained from Wireline formation testers, core permeability. This permeability measurement was also supplemented with permeability computed from Stoneley wave energy. NMR results also indicated presence of minor bitumen/very heavy hydrocarbon in certain zones which is further validated with visual observation of cores under UV light. Later the permeability results were calibrated with Core permeability and helped to conclude on the presence of heavier hydrocarbons. The integrated analysis allowed us to identify the best flow units over the entire interval and there by optimizing the completion strategy.