Evaluating Conceptual Plays

2008 ◽  
Author(s):  
P.J. Lee
Keyword(s):  
Process Models ◽  
Marginal Probability ◽  
Petroleum Resource ◽  
Exploration Risk ◽  
Geological Information ◽  
Cap Rock ◽  
Geological Factors ◽  
Geological Factor ◽  
Discovery Process Models ◽  
Reservoir Facies

A conceptual play has not yet been proved through exploration and can only be postulated from geological information. An immature play contains several discoveries, but not enough for discovery process models (described in Chapter 3) to be applied. The amount of data available for evaluating a conceptual play can be highly variable. Therefore, the evaluation methods used are related to the amount and types of data available, some of which are listed in Table 5.1. Detailed descriptions of these methods are beyond the scope of this book. However, an overview of these and other methods will be presented in Chapter 7. This chapter deals with the application of numerical methods to conceptual or immature plays. For immature plays, discoveries can be used to validate the estimates obtained. In this chapter, the Beaverhill Lake play and a play from the East Coast of Canada are examined. A play consists of a number of pools and/or prospects that may or may not contain hydrocarbons. Therefore, associated with each prospect is an exploration risk that measures the probability of a prospect being a pool. Estimating exploration risk in petroleum resource evaluation is important. Methods for quantifying exploration risks are described later. Geological factors that determine the accumulation of hydrocarbons include the presence of closure and of reservoir facies, as well as adequate seal, porosity, timing, source, migration, preservation, and recovery. For a specific play, only a few of these factors are recognized as critical to the amount of final accumulation. Consequently, if a prospect located within a sandstone play, for example, were tested, it might prove unsuccessful for any of the following reasons: lack of closure, unfavorable reservoir facies, lack of adequate source or migration path, and/or absence of cap rock. The frequency of occurrence of a geological factor can be measured from marginal probabilities. For example, if the marginal probability for the presence-of-closure factor is 0.9, there is a 90% chance that prospects drilled will have adequate closure. For a prospect to be a pool, the simultaneous presence of all the geological factors in the prospect is necessary. This requirement leads us to exploration risk analysis.

Concluding Remarks

2008 ◽  
Author(s):  
P.J. Lee
Keyword(s):  
Statistical Models ◽  
Finite Population ◽  
Pool Size ◽  
Process Models ◽  
Discovery Process ◽  
Feedback Mechanisms ◽  
Petroleum Resource ◽  
Petroleum Resources ◽  
Discovery Process Models ◽  
Interactive Loop

The procedure and steps of petroleum resource assessment involve a learning process that is characterized by an interactive loop between geological and statistical models and their feedback mechanisms. Geological models represent natural populations and are the basic units for petroleum resource evaluation. Statistical models include the superpopulation, finite population, and discovery process models that may be used for estimating the distributions for pool size and number of pools, and can be estimated from somewhat biased exploration data. Methods for assessing petroleum resources have been developed using different geological perspectives. Each of them can be applied to a specific case. When we consider using a particular method, the following aspects should be examined: • Types of data required—Some methods can only incorporate certain types of data; others can incorporate all data that are available. • Assumptions required—We must study what specific assumptions should be made and what role they play in the process of estimation. • Types of estimates—What types of estimates does the method provide (aggregate estimates vs. pool-size estimates)? Do the types of estimates fulfill our needs for economic analysis? • Feedback mechanisms—What types of feedback mechanism does the method offer? PETRIMES is based on a probabilistic framework that uses superpopulation and finite population concepts, discovery process models, and the optional use of lognormal distributions. The reasoning behind the application of discovery process models is that they offer the only known way to incorporate petroleum assessment fundamentals (i.e., realism) into the estimates. PETRIMES requires an exploration time series as basic input and can be applied to both mature and frontier petroleum resource evaluations.

Knowledge Discovery Process Models

2012 ◽  
pp. 72-100 ◽  
Author(s):  
Mouhib Alnoukari ◽  
Asim El Sheikh
Keyword(s):  
Life Cycle ◽  
Knowledge Discovery ◽  
Process Model ◽  
Common Factor ◽  
Final Outcome ◽  
Process Models ◽  
Data Driven ◽  
Discovery Process ◽  
The Common ◽  
Discovery Process Models

Knowledge Discovery (KD) process model was first discussed in 1989. Different models were suggested starting with Fayyad’s et al (1996) process model. The common factor of all data-driven discovery process is that knowledge is the final outcome of this process. In this chapter, the authors will analyze most of the KD process models suggested in the literature. The chapter will have a detailed discussion on the KD process models that have innovative life cycle steps. It will propose a categorization of the existing KD models. The chapter deeply analyzes the strengths and weaknesses of the leading KD process models, with the supported commercial systems and reported applications, and their matrix characteristics.

Three different approaches to provide urban geological information from a geological survey perspective: the Catalan case study

2020 ◽  
Author(s):  
Guillem Subiela ◽  
Miquel Vilà ◽  
Roser Pi ◽  
Elena Sánchez
Keyword(s):  
Urban Areas ◽  
Geological Survey ◽  
Anthropogenic Activity ◽  
Geological Environment ◽  
Borehole Data ◽  
Geological Information ◽  
Geological Factors ◽  
Geological Map ◽  
The Government

<p>Studying urban geology is a key way to identify municipal issues involved with urban development and sustainability, land resources and hazard awareness in highly populated areas. In the last decade, one of the lines of work of the Catalan Geological Survey (Institut Cartogràfic i Geològic de Catalunya) has been the development of (i) 1:5.000 scale Urban Geological Map of Catalonia project. Besides, two pilot projects have recently been started: (ii) the system of layers of geological information and (iii) the fundamental geological guides of municipalities. This communication focuses on the presentation of these projects and their utility, with the aim of finding effective ways of transferring geological knowledge and information of a territory, from a geological survey perspective.</p><p>The 1:5.000 urban geological maps of Catalonia (i) have been a great ambitious project focused on providing detailed, consistent and accurate geological, geotechnical and anthropogenic activity information of the main urban areas of Catalonia. Nevertheless, it must be taken into account that the compilation and elaboration of a large volume of geological information and also the high level of detail require a lot of time for data completeness.</p><p>In order to optimize a greater distribution of information, a system of layers of geological information (ii) covering urban areas is being developed. This pilot project consists of providing specific layers of Bedrock materials, Quaternary deposits, anthropogenic grounds, structural measures, geochemical compositions, borehole data and so on. However, as information layers are treated individually, it may not be clear the coherence between data from different layers of information and its use is currently limited to Earth-science professionals working with geological data.</p><p>Hence, as a strategy to reach a wider range of users and also provide a homogeneous and varied geological information, the development of fundamental geological guides for municipalities is also being carried out (iii). These documents include the general geological characterization of the municipality, the description of the main geological factors (related to geotechnical properties, hydrogeology, environmental concerns and geological hazards and resources) and the list of the sources of geological information to be considered. Moreover, each guide contains a 1:50.000 geological map that has cartographic continuity with the neighbouring municipalities. The municipal guides allow a synthesis of the geological environment of the different Catalan municipalities and give fundamental recommendations for the characterization of the geological environment of the municipality.</p><p>In conclusion, the three projects facilitate the characterization of geological environment of urban areas, the evaluation of geological factors in ground studies and also, in general, the management of the environment. These products differ depending on the degree of detail, the coherence of the geological information, the necessary knowledge for their execution or their purpose of use. This set of projects defines a geological urban framework, which is adjusted depending on the government’s requirements, the society’s needs and the geological survey’s available resources.</p>

scholarly journals Mineralogical and Geochemical Characteristics of Lithium and Rare Earth Elements in High-Sulfur Coal from the Donggou Mine, Chongqing, Southwestern China

Minerals ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. 627
Author(s):  
Jianhua Zou ◽  
Longfei Cheng ◽  
Yuanchen Guo ◽  
Zhengcheng Wang ◽  
Heming Tian ◽  
...  
Keyword(s):  
Rare Earth ◽  
Rare Earth Elements ◽  
Raw Materials ◽  
Geochemical Characteristics ◽  
Critical Elements ◽  
Geological Factors ◽  
Potential Alternative ◽  
Geological Factor ◽  
Alternative Sources ◽  
Coal Measures

Coal and coal by-products are considered as the potential raw materials for critical elements (e.g., rare earth elements, Li, Ga, Ge, etc.), which have attracted much attention in recent years. The purpose of this study is to investigate the mineralogical and geochemical characteristics, and controlling geological factors of lithium and rare earth elements in the Lopingian (Wujiaping Formation) coal from the Donggou Mine, southeastern Chongqing Coalfield, China. Results indicate that lithium and rare earth elements are significantly enriched in the Donggou coals, which could be new potential alternative sources for critical elements. Concentrations of lithium and rare earth elements in the Donggou coals gradually increase from top to bottom. Lithium is mainly associated with kaolinite, while rhabdophane, florencite, goyazite, and xenotime are the main hosts of rare earth elements. The controlling geological factor is the groundwater leaching of underlying tuff, and to a lesser extent, the terrigenous clastic materials input from the top layer of the Kangdian Upland. This study provides mineralization information for lithium and rare earth elements exploration in coal measures.

A survey of data mining and knowledge discovery process models and methodologies

2010 ◽  
Vol 25 (2) ◽  
pp. 137-166 ◽  
Author(s):  
Gonzalo Mariscal ◽  
Óscar Marbán ◽  
Covadonga Fernández
Keyword(s):  
Data Mining ◽  
Knowledge Discovery ◽  
Scientific Literature ◽  
State Of The Art ◽  
Process Models ◽  
Knowledge Discovery In Databases ◽  
Discovery Process ◽  
Advantages And Disadvantages ◽  
Discovery Process Models ◽  
Discovery Project

AbstractUp to now, many data mining and knowledge discovery methodologies and process models have been developed, with varying degrees of success. In this paper, we describe the most used (in industrial and academic projects) and cited (in scientific literature) data mining and knowledge discovery methodologies and process models, providing an overview of its evolution along data mining and knowledge discovery history and setting down the state of the art in this topic. For every approach, we have provided a brief description of the proposed knowledge discovery in databases (KDD) process, discussing about special features, outstanding advantages and disadvantages of every approach. Apart from that, a global comparative of all presented data mining approaches is provided, focusing on the different steps and tasks in which every approach interprets the whole KDD process. As a result of the comparison, we propose a new data mining and knowledge discovery process namedrefined data mining processfor developing any kind of data mining and knowledge discovery project. The refined data mining process is built on specific steps taken from analyzed approaches.

Two decades of Geological Survey of Canada petroleum resource assessments

1993 ◽  
Vol 30 (2) ◽  
pp. 321-332 ◽  
Author(s):  
P. J. Lee
Keyword(s):  
Monte Carlo ◽  
Sedimentary Basins ◽  
Process Models ◽  
Petroleum Exploration ◽  
Geological Survey ◽  
Geochemical Data ◽  
Cumulative Probability ◽  
Data Set ◽  
Petroleum Resource ◽  
Pool Sizes

The Geological Survey of Canada has conducted petroleum resource assessments of Canadian sedimentary basins to respond to a need for information concerning the extent of Canada's energy endowment. The evolution of these activities and methods, which began in the 1970's and continue to the present, is discussed in this paper. The first assessment of Canadian basins was conducted in the 1970's using a volumetric yield method, whereby the volume of sedimentary rock in a basin was multiplied by a hydrocarbon yield per unit volume factor. Later, a Monte Carlo approach was used. It required a knowledge of the exploration plays in a given basin and made use of a variety of pool parameters expressed as cumulative probability distributions. The Monte Carlo method did not account for the biased data-set problem that came from using a selective exploration process. A third assessment method was based on geochemical data and was used to estimate the amount of hydrocarbon generated and the expulsion efficiencies. The results from each of the three methods defied detailed economic analysis.Advanced statistical methods were gradually developed in the 1980's. By the end of this period, PETRIMES (the Petroleum Exploration and Resource Evaluations System) was developed. This system evaluates hydrocarbon potential by means of an exploration play definition coupled with compiled play data used to estimate undiscovered pool sizes. During this period, discovery process models were developed to account for the biased data. Estimations of individual pool sizes in the play were made and displayed graphically so that undiscovered pools could be identified in a statistically derived population of pools. Summed quantities of petroleum in undiscovered pools were used to define remaining expected play potential.The estimated undiscovered individual pool sizes inferred from assessments serve as direct input to economic analyses that examine which pools are viable prospects under specific economic conditions. This knowledge is useful to governments formulating energy policies and to petroleum companies setting exploration priorities.

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