1 Introduction

Since the explosion of the Internet, there is a huge interest in designing websites which allow users to easily find what they are seeking and to help web analysts in the decision making process. Web Analytic tools facilitate understanding and the discovery of patterns that lay beneath a website, but they are cumbersome to understand since they do not make extensive use of Information Visualization (InfoVis) techniques. The mechanisms provided by current visualization systems allow for the support required for data recovery that is needed for providing archiving of data and provide ease of data recovery, data recall as well as interesting visualizations and reusing archived visualizations [1]. However, visualization systems do not provide support for the conceptualization process related creating and maintaining awareness during the visual exploration process. The process of visual exploration help analyst with specifics for purpose-based visualization of data, i.e., exploration data or development data.

Traditional maps present geospatial data and can deliver understanding into location-based trends and patterns. However, maps can now be used to motivate deeper conceptualization and location-based geospatial patterns, relationships, and trends. A new role of maps in science, decision-making, policy formulation and as a visual thinking/decision-support tool is being adopted widely. Geovisualization as it relates to the new dimension of using maps, through addressing the visual investigation, visual analysis, in addition to the synthesis and presentation of geospatial data through integrating interdisciplinary approaches [2] (e.g. cartography, image analysis, information visualization, visual analytics, and GIScience).

2 Methods

A contemporary approach to dealing with various, complex information is that of Geovisual analytics. It is the combination of human intuition and abstract visual metaphors. Visual analytics stems from scientific and information visualization but also includes technologies from other fields such as, management, statistical analysis, cognitive science, decision science, it allows for. This research attempts to address some basic issues as they relate to geovisual analytics for Petroleum Data Management (PDM). This is through multi-dimensional models, as a standalone models or as a web-based information visualization and search context. This can allow for effective digital archiving of fields and operations zones are active from the historical documents and reports that can be used on ad hoc basis. It allows category-based or field-based search to address short-term and long-term interests based on the task level and to represent it according to the enterprise level requirements [3]. Geospatial visualization capabilities expand the 1-dimensional information space to 2- or 3- dimensional representations of retrieved results and it can provide combination of user modelling and visualization to develop an approach to assist human users in their search process. The scope of this research attempts to link the traditional geovisual analytics approaches to application specific domain, as it relates to Petroleum Data Management (PDM), and provide strategic agenda for potential research issues that are domain specific, as they relate to petroleum exploration and production, “Fig. 1” is showing petroleum data requirements.

Fig. 1
figure 1

Petroleum data examples

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3 Results

3.1 Petroleum Big Data Management (PDM)

Petroleum data management attempts to provide GIS-based system for archiving, and indexing all relevant data with reference to their ground coordinates. This provides extensive database for well logs, seismic sections, technical reports, production reports, maintenance, and follow-up data in addition to various additional sources of data that can be stored, and recalled and visualized to provide specific knowledge about specific location, as it relates to:

  1. 1.

    Spatiotemporal discovery systems that allow for multiple scenario visualization.

  2. 2.

    Tagging and annotation systems that display detailed attributes.

  3. 3.

    Web-based annotation, tagging and annotation capabilities.

3.2 Visual Analytics Capabilities

Traditional GIS systems are to some extent are incapable of coping with the size and complexity data, which requires reduction of the map layer or data for effective use [4], this has triggered the need for new cross-disciplinary methods (e.g. geovisualization, information visualization, data mining, and cartography). ‘Geovisual Analytics for Spatial Decision Support’ is the name that is adopted for this interdisciplinary approach that address providing computer support to solving geospatial decision issues through enhancing human computer integration to visualize, analyses, and interpret information. Table 1 is showing these challenges.

Table 1 Challenges for geovisual analytics decision support
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The distinction between Geovisual Analytics for Spatial Decision Support and Visual Analytics: 1. Complexity of spatiotemporal space, 2. The interdisciplinary scope, and 3. Level of date exploration and knowledge generation. These distinction are relatively addressed by traditional GIS. However, they require sizeable reduction in size and complexity of data, which justifies the need to find a way out of this forced simplification.

4 Discussion

Normally, decision-making process involves various stakeholders with different roles, interests, levels of knowledge of the problem domain and the territory, and experiences in using visualization and analytical tools. The three main players are [5]:

  1. 1.

    Top management decision-makers (administrators/executives)—who often have constraints to gather data, analyze information, and thoroughly evaluate options.

  2. 2.

    Analysts—They normally present results of their analysis to the decision-maker, informing the decision-maker about why they chose a certain option over others. Visual representations and/or ‘what-if’ scenario, and comparison of options can be valuable for effective communication of information

  3. 3.

    Stakeholders (decision-makers and organizations that can be affected by the decisions made)—they need to be included in the analysis process. They also need an effortlessly clear demonstration of information and simply practical information display facilities [6]; in some situations, more tailored visualization might be necessary.

5 Conclusion

Although some research issues have been mentioned, there is progressive need for convincing comprehensive solutions that address the significant advances in creating tools as well as in developing the theory of geovisual analysis. This is a multidisciplinary team’s effort. The research in this paper cover a spectrum of the research themes that conceptually necessary for the discussions to highlight how Geovisual Analysis can be integrated as effective interdisciplinary tool for Decision-makers in petroleum industry.