This book describes procedures for determining the total hydrocarbon (petroleum) resource or resource potential in a region. Statistical concepts and methods employed in petroleum resource assessment are the subject of the manuscript, extensively illustrated by numerous real case studies. Prof. Lee's computer-aided Petroleum Information Management and Resource Evaluation System (PETRIMES) methodology has been adopted by governments around the world and by major multinational oil companies to perform resource assessment and to predict future oil and gas production. Though this methodology is so widely used, there is no "user's guide" to it, and this book will be the definitive resource for PETRIMES users.

This volume contains the edited papers prepared by lecturers and participants of the NATO Advanced Study Institute on "Statistical Treatments for Estimation of Mineral and Energy Resources" held at II Ciocco (Lucca), Italy, June 22 - July 4, 1986. During the past twenty years, tremendous efforts have been made to acquire quantitative geoscience information from ore deposits, geochemical, geophys ical and remotely-sensed measurements. In October 1981, a two-day symposium on "Quantitative Resource Evaluation" and a three-day workshop on "Interactive Systems for Multivariate Analysis and Image Processing for Resource Evaluation" were held in Ottawa, jointly sponsored by the Geological Survey of Canada, the International Association for Mathematical Geology, and the International Geological Correlation Programme. Thirty scientists from different countries in Europe and North America were invited to form a forum for the discussion of quantitative methods for mineral and energy resource assessment. Since then, not only a multitude of research projects directed toward quantitative analysis in the Earth Sciences, but also recent advances in hardware and software technology, such as high-resolution graphics, data-base management systems and statistical packages on mini and micro-computers, made it possible to study large geoscience data sets. In addition, methods of image analysis have been utilized to capture data in digital form and to supply a variety of tools for charaterizing natural phenomena.

The petroleum industry is enduring difficult financial times because of the continuing depressed price of crude oil on the world market. This has caused major corporate restructuring and reductions in staff throughout the industry. Because oil exploration must now be done with fewer people under more difficult economic constraints, it is essential that the most effective and efficient procedures be used. Computing Risk for Oil Prospects describes how prospect risk assessment — predicting the distribution of financial gains or losses that may result from the drilling of an exploration well — can be done using objective procedures implemented on personal computers. The procedures include analyses of historical data, interpretation of geological and geophysical data, and financial calculations to yield a spectrum of the possible consequences of decisions. All aspects of petroleum risk assessment are covered, from evaluating regional resources, through delineating an individual prospect, to calculation of the financial consequences of alternative decisions and their possible results. The bottom lines are given both in terms of the probable volumes of oil that may be discovered and the expected monetary returns. Statistical procedures are linked with computer mapping and interpretation algorithms, which feed their results directly into routines for financial analysis. The programs in the included library of computer programs are tailored to fit seamlessly together, and are designed for ease and simplicity of operation. The two diskettes supplied are IBM compatible. Full information on loading is given in Appendix A - Software Installation. Risk I diskette contains data files and executables and Risk 2 diskette contains only executables. The authors contend that the explorationist who develops a prospect should be involved in every facet of its analysis, including risk and financial assessments. This book provides the tools necessary for these tasks.

Volume 1 presents the mathematics and general engineering and science of petroleum engineering. It also examines the auxiliary equipment and provides coverage of all aspects of drilling and well completion.

This guide to small area estimation aims to help users compile more reliable granular or disaggregated data in cost-effective ways. It explains small area estimation techniques with examples of how the easily accessible R analytical platform can be used to implement them, particularly to estimate indicators on poverty, employment, and health outcomes. The guide is intended for staff of national statistics offices and for other development practitioners. It aims to help them to develop and implement targeted socioeconomic policies to ensure that the vulnerable segments of societies are not left behind, and to monitor progress toward the Sustainable Development Goals.

Quantitative resource assessment methods play an increasing role in exploration for petroleum, water and minerals. This volume presents an international review on the state-of-the-art of the computerized methodology in resource exploration. The papers taken from those presented at the symposium are classified to either techniques, i.e., trend analysis; classification techniques; geostatistics; image analysis; expert systems/artificial intelligence; inventories; tomography and others, or to resources, i.e., petroleum, water, metals and non-metals.

The environment for obtaining information and providing statistical data for policy makers and the public has changed significantly in the past decade, raising questions about the fundamental survey paradigm that underlies federal statistics. New data sources provide opportunities to develop a new paradigm that can improve timeliness, geographic or subpopulation detail, and statistical efficiency. It also has the potential to reduce the costs of producing federal statistics. The panel's first report described federal statistical agencies' current paradigm, which relies heavily on sample surveys for producing national statistics, and challenges agencies are facing; the legal frameworks and mechanisms for protecting the privacy and confidentiality of statistical data and for providing researchers access to data, and challenges to those frameworks and mechanisms; and statistical agencies access to alternative sources of data. The panel recommended a new approach for federal statistical programs that would combine diverse data sources from government and private sector sources and the creation of a new entity that would provide the foundational elements needed for this new approach, including legal authority to access data and protect privacy. This second of the panel's two reports builds on the analysis, conclusions, and recommendations in the first one. This report assesses alternative methods for implementing a new approach that would combine diverse data sources from government and private sector sources, including describing statistical models for combining data from multiple sources; examining statistical and computer science approaches that foster privacy protections; evaluating frameworks for assessing the quality and utility of alternative data sources; and various models for implementing the recommended new entity. Together, the two reports offer ideas and recommendations to help federal statistical agencies examine and evaluate data from alternative sources and then combine them as appropriate to provide the country with more timely, actionable, and useful information for policy makers, businesses, and individuals.