Knowledge-Based Scientific Discovery in Geological Databases
نویسندگان
چکیده
A framework for knowledge-based scienti c discovery in geological databases has been developed. The discovery process consists of two main steps: context de nition and equation derivation. Context de nition properly de nes and formulates homogeneous regions, each of which is likely to produce a unique and meaningful analytic formula for the goal variable. Clustering techniques and a suite of visualization and interpretation routines make up a tool box that assists the context de nition task. Within each context, multi-variable regression analysis is conducted to derive analytic equations between the goal variable and a set of relevant independent variables, starting with one or more of the initial base models. Domain knowledge, plus a heuristic search technique called component plus residual plots dynamically guide the equation re nement process. The methodology has been applied to derive porosity equations for data collected from oil elds in the Alaska Basin. Preliminary results demonstrate the e ectiveness of this method-
منابع مشابه
A Framework for Scientific Discovery in Geological Databases
It is common knowledge in the oil industry that the typical cost of drilling a new offshore well is in the range of $30-40 million, but the chance of that site being an economic success is 1 in 10. Recent advances in drilling technology and data collection methods have led to oil companies and their ancillary companies collecting large amounts of geophysical/geological data from production well...
متن کاملLITHOTHEQUE knowledge system about world-s mineral deposits supported by miniaturized sample sets: call for international adoption, networking and exchange
Our civilization is based on metals, among other life supports. The existing ore deposits are becoming rapidly depleted by almost exponentially increasing demand and production and major new ore discoveries are needed. Mineral exploration is supported by modern tools and scientific ideas, but geological characteristics of orebodies and their rock associations have still to be visualized.The tim...
متن کاملApplication of Rough Set Theory in Data Mining for Decision Support Systems (DSSs)
Decision support systems (DSSs) are prevalent information systems for decision making in many competitive business environments. In a DSS, decision making process is intimately related to some factors which determine the quality of information systems and their related products. Traditional approaches to data analysis usually cannot be implemented in sophisticated Companies, where managers ne...
متن کاملAnalysis of User Interface Environment in Scientific Databases According to the Viewpoints of Postgraduate Students Applying Dervin's Sense-Making Theory
Abstract Background and purpose: The purpose of this study was to analyze the user interface environment of some databases (Science Direct, Springer, Clinical Key, and Wiley online library) from the perspective of users applying Dervin's sense-making theory. Materials and methods: A cross-sectional descriptive study was conducted in 100 PhD students and research-based PhD students in Mazandar...
متن کاملA Knowledge-Driven Geospatially Enabled Framework for Geological Big Data
Geologic survey procedures accumulate large volumes of structured and unstructured data. Fully exploiting the knowledge and information that are included in geological big data and improving the accessibility of large volumes of data are important endeavors. In this paper, which is based on the architecture of the geological survey information cloud-computing platform (GSICCP) and big-data-rela...
متن کامل