Seakeeping assessment of fishing vessels in conceptual design stage

The main idea of this paper is to identify functional relations between seakeeping characteristics and hull form parameters of Mediterranean fishing vessels. Multiple regression analysis is used for quantitative assessment through a computer software that is based on the SQL Server Database. The seakeeping attributes under investigation are the transfer functions of heave and pitch motions and of absolute vertical acceleration at stern, while the ship parameters influencing motion dynamics have been classified into two groups: displacement (Δ) and main dimensions (L, B, T), coefficients that define the details of the hull form (C_WP, C_VP, LCB, LCF, etc.).Four multiple regression models having different parameter combinations are here investigated and discussed, giving way to the so-called ‘Simple Model’, ‘Intermediate Model’, ‘Enhanced 1 Model’ and ‘Enhanced 2 Model’. The obtained results are more than satisfactory for seakeeping predictions during the conceptual design stage.     

Dynamic data integration for structural modeling: model screening approach using a distance-based model parameterization

This paper proposes a novel history-matching method where reservoir structure is inverted from dynamic fluid flow response. The proposed workflow consists of searching for models that match production history from a large set of prior structural model realizations. This prior set represents the reservoir structural uncertainty because of interpretation uncertainty on seismic sections. To make such a search effective, we introduce a parameter space defined with a “similarity distance” for accommodating this large set of realizations. The inverse solutions are found using a stochastic search method. Realistic reservoir examples are presented to prove the applicability of the proposed method.     

Glacio-lacustrine stratigraphy,aquifer characterization and contaminant transport: a case study in South Lake Tahoe,California, USA

A hydrogeologic model that has been used by many researchers and consultants to describe an area of South Lake Tahoe, California, USA impacted by MTBE contamination describes a relatively homogeneous unconfined aquifer comprised of poorly sorted glacial outwash deposits, within which water-supply wells are able to exert significant alteration in natural groundwater flow. A re-examination of the area’s hydrogeology is presented, which supports a layered heterogeneous aquifer system constructed of alternating fine and coarser-grained glacio-lacustrine depositional units. This re-evaluation was accomplished through a review of lithologic logs across an area of approximately 1 km², combined with observations of significant hydraulic head differences and knowledge of the depositional environments controlled by Pleistocene Lake Tahoe high stands. Many of the fine-grained units observed at depths from 6 to 15 m, although relatively thin, are generally continuous and serve as significant barriers to groundwater flow. The vertical migration of contamination across these fine-grained units to deeper groundwaters was facilitated by cross-screened monitoring wells installed as part of site investigation activities. This conclusion highlights the importance of geologic characterization and proper monitoring well construction at contaminated site investigations.

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Uncertainty as the overlap of alternate conditional distributions

An important task in modern geostatistics is the assessment and quantification of resource and reserve uncertainty. This uncertainty is valuable support information for many management decisions. Uncertainty at specific locations and uncertainty in the global resource is of interest. There are many different methods to build models of uncertainty, including Kriging, Cokriging, and Inverse Distance. Each method leads to different results. A method is proposed to combine local uncertainties predicted by different models to obtain a combined measure of uncertainty that combines good features of each alternative. The new estimator is the overlap of alternate conditional distributions.     

Bayesian estimation of seismic hazard for two sites in Switzerland

Seismic hazard analysis is based on data and models, which both are imprecise and uncertain. Especially the interpretation of historical information into earthquake parameters, e.g. earthquake size and location, yields ambiguous and imprecise data. Models based on probability distributions have been developed in order to quantify and represent these uncertainties. Nevertheless, the majority of the procedures applied in seismic hazard assessment do not take into account these uncertainties, nor do they show the variance of the results. Therefore, a procedure based on Bayesian statistics was developed to estimate return periods for different ground motion intensities (MSK scale).Bayesian techniques provide a mathematical model to estimate the distribution of random variables in presence of uncertainties. The developed method estimates the probability distribution of the number of occurrences in a Poisson process described by the parameter . The input data are the historical occurrences of intensities for a particular site, represented by a discrete probability distribution for each earthquake. The calculation of these historical occurrences requires a careful preparation of all input parameters, i.e. a modelling of their uncertainties. The obtained results show that the variance of the recurrence rate is smaller in regions with higher seismic activity than in less active regions. It can also be demonstrated that long return periods cannot be estimated with confidence, because the time period of observation is too short. This indicates that the long return periods obtained by seismic source methods only reflects the delineated seismic sources and the chosen earthquake size distribution law.     

Redefining active volcanoes: a discussion

The analysis of the current definitions of active volcanoes indicates that they are empirical, conventional, inaccurate, nongeological, and arbitrarily constraining. Redefinition is therefore needed. One possible approach is to refine the current empirical definitions. A statistically reasonable and practical redefinition using a geologically based time convention-Holocene or 10000 years-is suggested. A set of time conditions according to volcano typology-i.e. 1000; 10000 and 100000 years for high-frequency basaltic shields, andesitic-dacitic composite volcanoes and low-frequency large silicic calderas, respectively-as further refinement of the empirical definition is also envisaged. Devising a phenomenological definition as a theoretical approach is another possibility, but in practice extant diagnostic means are still unsatisfactory to discriminate accurately between dormant and extinct volcanoes. As a consequence of the redefinition, a classification of volcanoes according to their eruptive status is proposed. Redefinition of active volcanoes might increase accuracy in the usage of basic terms in volcanology and influence volcanic hazard assessment and risk mitigation projects.     

Une approche innovante pour modéliser la biodégradation des composés organochlorés volatils en aquifères poreux

The goal of this study was to develop an innovative chloroethene biodegradation module based on biological, thermodynamical and mechanistic concepts. The biodegradation scheme was based on the postulate that in each part of an aquifer only one degradation mechanism is dominant: the one involving the most energetic electron acceptor. Thus, the selection of the active degradation mechanism was a function of the concentration of different electron acceptors. Modified Monod-type kinetics was used in order to take into account the possible influence of some compounds on the biodegradation of a given organic compound. The numerical model developed was applied to a simple test case, whose results are presented here. To cite this article: F. Nex et al., C. R. Geoscience 338 (2006).     

Optimization of nonconventional wells under uncertainty using statistical proxies

The determination of the optimal type and placement of a nonconventional well in a heterogeneous reservoir represents a challenging optimization problem. This determination is significantly more complicated if uncertainty in the reservoir geology is included in the optimization. In this study, a genetic algorithm is applied to optimize the deployment of nonconventional wells. Geological uncertainty is accounted for by optimizing over multiple reservoir models (realizations) subject to a prescribed risk attitude. To reduce the excessive computational requirements of the base method, a new statistical proxy (which provides fast estimates of the objective function) based on cluster analysis is introduced into the optimization process. This proxy provides an estimate of the cumulative distribution function (CDF) of the scenario performance, which enables the quantification of proxy uncertainty. Knowledge of the proxy-based performance estimate in conjunction with the proxy CDF enables the systematic selection of the most appropriate scenarios for full simulation. Application of the overall method for the optimization of monobore and dual-lateral well placement demonstrates the performance of the hybrid optimization procedure. Specifically, it is shown that by simulating only 10% or 20% of the scenarios (as determined by application of the proxy), optimization results very close to those achieved by simulating all cases are obtained.