Major aim is to construct a comprehensive map of the allocation of oil and gas fields with large reserves for further analogy estimation and reconstruction of geological history. The main contribution of this work is the development of a multidimensional and multilevel database and the corresponding GIS Project for visualization.
The set of multidisciplinary backgrounds in combination with a spatial algorithmic tools are used as a basis for an analytical study of worldwide hydrocarbon occurrences and estimation establishment of petroleum industry. Creating and support of verified databases is one of the priorities for the development of geoinformatics.
A database provides the availability of reliable and comparable data as a prerequisite for effective analysis on issues affecting oil and gas industry. However, before approaching the issue of elaborating the idea of creation a thematically oriented database, the authors solved a number of challenges related directly to the data — their search, collection, systematization, storage and management for the purpose of further analysis.
The primary objective of ROSA GIS Project is to investigate and evaluate the distribution of oil and gas in the world, identify their accumulations, compare the history of geological development and conduct a large-scale analytical study. Due to economical, political and other reasons investigated data could be slightly associated with the classic definitions of Big Data Roberts That opens new challenges in the way we search, manage and analyze data. Presented approaches could be further applied to other fields where the data is not well distributed within research community.
In our Project the data are treated as a strategic asset. Therefore, it is important to approve a number of principles that could help to organize a methodical process of extracting and systematizing the necessary data. As a part of the Project implementation, the authors discovered that guidelines on aggregation, systematization, improvement and analysis of ROSA data set were positively correlated with FAIR principles Findable, Accessible, Interoperable and Reusable despite the fact that original oil and gas data by its nature do not meet those principles.
One of the tools that helps to meet the described above requirements is Systems Analysis SA. We used various methods and approaches of SA to collect and integrate data, as well as to approve the structure of the ROSA database for further studies.
To advance the tools for data analysis the database is constructed as multidimensional and multilevel environment. The first one reflects the multidimensional space of database parameters describing the deposits. Multilevel is attributable primarily to the rank of deposits according to the volume of reserves levels ROSA 1.
Creation of the web service for the further visualization of the ROSA database objects and its attributive information in the ArcGIS environment allows to present all deposits as a single world map with various base maps and provides a user with various spatial algorithmic tools for data analysis. Our goal is to introduce and combine heterogeneous data in a unified manner and to represent oil and gas information that is well coordinated through each of the FAIR principles.
Metadata and data of the ROSA GIS Project are findable for both researchers and computers by their description with a plurality of accurate and relevant attributes.
The use of keywords and cross-cutting parameters for all levels of the database makes the data handling much easier and data files more findable for users. Creation of the web service provides users with the capacity to access data without a need to install any specific software.
Thus, the data access protocol is open, free, and universally implementable. In addition, the protocol allows for authentication and authorisation procedure, as appropriate.
It allows to compare and correlate oil and gas data with numerous spatial and other data on infrastructure, economy, climate, etc. Advanced algorithmic toolbox of the web service extends basic data storage and visualization features and enables its further processing and more sophisticated analysis. In addition, all heterogeneous data are reduced to a common standard of petroleum industry for further possibility of replicated sampling and combining in different settings and models.
Furthermore, ROSA database is fitted with bibliography guide to authenticate or discover data provenance and quality. Data collection and its further analysis will remain challenging in various aspects. Among a major barriers to data collection is low availability of data, due to the specific nature of the data and their secrecy, particularly in the case of Near and Middle East countries. Therefore, some fields of attribute tables of ROSA database appear insufficiently representative.
Sometimes null values empty fields can be found in database. Another challenge is data integration. Since the data come from diverse sources in different languages in a variety of formats textual and graphic material and standards, special attention should be paid to converting data to the unified standard.
Significant number of differences between Russian and foreign terminology should be also taken into account. One example is the classification of deposits according to their reserves. In the global oil and gas industry, the classifiers of the above indicators and their units of measure are significantly different. Thus, the principle of data unification is extremely important to overcome semantic and technical differences.
Another important issue is the data reliability. As many sources include contradictions, the data collection should be accurate and avoid invalid sources. For the verification purpose ROSA database is linked to bibliographic summary that testifies the reliability of obtained results and provides an efficient tool for its further analysis.
Consequently, data used in the ROSA Project should have an appropriate systematization model enabling unified data comparison from a single point of view for their further merging and harmonization.
The ROSA database requires a system approach to overcome the challenges listed above and at the same time meets the requirements of the comprehensive investigation of the oil and gas industry development. A proper model should be established to provide a data comparison for its further matching and merging. Scientific knowledge is much more than a simple compilation of data units.
Among the key issues is the way we manage the data. The application of system analysis methods is the most effective tool that allows to systematize data for conducting further extensive analysis.
In this way, to advance data analysis tools, the database represents multidimensional and multilevel structure. In keeping with these principles in the first phase of the Project a number of subtasks were carried out in order to efficiently organize and compile a geospatial database.
The database objects were the largest oil and gas fields in Russia and other countries in the 20 and 21 centuries. Adherence to the given principles makes the database as verified as possible due to a better control of the quality of data. We made a comprehensive literature review covering over open specialized Russian and foreign bibliographic sources and as a result, an annotated bibliography was compiled. Originally, however, all sources are scattered. They are not user-friendly and do not offer the possibility of immediate input for analysis.
Table 1 provides an example of collecting, converting, unifying and validating the heterogeneous data in machine-readable form for unmanned processing. Both are taken from ROSA 1.
As we can see, each object from ROSA 1. This makes it possible to distribute the above data into groups for further classification of deposits and their independent analysis. To reflect the process of the oil and gas industry establishment and development more accurately the database attribute tables were constructed dividing all data into two types — static and dynamic.
The first information level ROSA 1. The second and third information levels ROSA 2. The proposed block diagram represents the interaction between all levels of the ROSA database Figure 1. The principle of the inverted pyramid is applied since there is gradual reduction of coverage and number of objects while the detail of the data is increased. Each object is characterized by unique and unified parameters.
Dynamic unit parameters include production methods, production technologies, technological features, well production rate. They vary with one-year step for the ROSA 1. Due to limited access to information, they are presented within one cell of the attribute table with a time step that is most appropriate for each specific field.
Another tool associated with the database provides end-to-end parameters, which ensure efficient navigation within all blocks and levels, and facilitates the processing of a large amount of heterogeneous data in both numerical and text formats. At the next stage of creating the database, the authors used a comprehensive geographic information system ArcGIS. It allows to geographically present all deposits in a single environment with various base maps and provides a user with the instrumentation to analyze the data using geospatial tools.
For this type of data, various standard ArcGIS geoprocessing tools can be used, for example:. In addition, more advanced geoprocessing tools for fuzzy clustering in a data set using Discrete Mathematical Analysis DMA can be used to analyze the deposits e.
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