Deep neural network application for 4D seismic inversion to changes in pressure and saturation: Optimizing the use of synthetic training datasets     

Gustavo Côrte  Jesper Dramsch  Hamed Amini  Colin MacBeth 《Geophysical Prospecting》2020,68(7):2164-2185

In this work, we tackle the challenge of quantitative estimation of reservoir dynamic property variations during a period of production, directly from four-dimensional seismic data in the amplitude domain. We employ a deep neural network to invert four-dimensional seismic amplitude maps to the simultaneous changes in pressure, water and gas saturations. The method is applied to a real field data case, where, as is common in such applications, the data measured at the wells are insufficient for properly training deep neural networks, thus, the network is trained on synthetic data. Training on synthetic data offers much freedom in designing a training dataset, therefore, it is important to understand the impact of the data distribution on the inversion results. To define the best way to construct a synthetic training dataset, we perform a study on four different approaches to populating the training set making remarks on data sizes, network generality and the impact of physics-based constraints. Using the results of a reservoir simulation model to populate our training datasets, we demonstrate the benefits of restricting training samples to fluid flow consistent combinations in the dynamic reservoir property domain. With this the network learns the physical correlations present in the training set, incorporating this information into the inference process, which allows it to make inferences on properties to which the seismic data are most uncertain. Additionally, we demonstrate the importance of applying regularization techniques such as adding noise to the synthetic data for training and show a possibility of estimating uncertainties in the inversion results by training multiple networks.  相似文献   

Ranking of Placer Gold Prospects in Chile Through Analytic Hierarchy Process     

Jara  J. Joaquín  Moreno  Francisco  Jara  Raúl  Dubournais  Francisco  Mata  Rodrigo  Peters  David  Marquardt  Carlos  Lagos  Gustavo 《Natural Resources Research》2019,28(3):813-832

Chile has a rich, but poorly known history of placer gold mining. At present, this sector is almost nonexistent and there are some restrictions for its revival: disperse and partial information on existing resources and limited technical expertise to assess the potential of placer gold mine sites. This paper presents the background, methodology and results of the prioritization process of known prospects of this kind in Chile. This research was part of a publicly funded project aimed to incentivize the development of this industry. The ranking was carried out using the analytic hierarchy process, which allowed to include different quantitative and qualitative variables related to the economic potential, technical aspects, contextual viability and socioeconomic factors in the analysis. The results show that, despite the increasing relevance of environmental and community issues in mining development, the business potential and the economic/technical aspects are the main factors in the early selection of a site to advance in exploration and development activities. Both variables represented around 40% and 37% of weights in the final selection, respectively. In contrast, contextual viability and local socioeconomic impacts only accounted for the remaining 23%. This study also shows that the inclusion of experts with different backgrounds in the process enriches the analysis and does not significantly distort the final outcome of the prioritization. Finally, the relevance of using MCDM tools when assessing the attractiveness of mine sites for their development is highlighted, particularly when public funds for subsequent exploration activities are committed.

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Long‐term sediment yield from a small catchment in southern Brazil affected by land use and soil management changes          下载免费PDF全文

Jean P.G. Minella  Gustavo H. Merten  Claúdia A.P. Barros  Rafael Ramon  Alexandre Schlesner  Robin T. Clarke  Michele Moro  Leandro Dalbianco 《水文研究》2018,32(2):200-211

Sediments produced from eroding cultivated land can cause on‐site and off‐site effects that cause considerable economic and social impacts. Despite the importance of soil conservation practices (SCP) for the control of soil erosion and improvements in soil hydrological functions, limited information is available regarding the effects of SCP on sediment yield (SY) at the catchment scale. This study aimed to investigate the long‐term relationships between SY and land use, soil management, and rainfall in a small catchment. To determine the effects of anthropogenic and climatic factors on SY, rainfall, streamflow, and suspended sediment concentration were monitored at 10‐min intervals for 14 years (2002–2016), and the land use and soil management changes were surveyed annually. Using a statistical procedure to separate the SY effects of climate, land use, and soil management, we observed pronounced temporal effects of land use and soil management changes on SY. During the first 2 years (2002–2004), the land was predominantly cultivated with tobacco under a traditional tillage system (no cover crops and ploughed soil) using animal traction. In that period, the SY reached approximately 400 t·km^?2·year^?1. From 2005 to 2009, a soil conservation programme introduced conservation tillage and winter cover crops in the catchment area, which lowered the SY to 50 t·km^?2·year^?1. In the final period (2010–2016), the SCP were partially abandoned by farmers, and reforested areas increased, resulting in an SY of 150 t·km^?2·year^?1. This study also discusses the factors associated with the failure to continue using SCP, including structural support and farmer attitudes.  相似文献   

The Juchatengo complex: an upper-level ophiolite assemblage of late Paleozoic age in Oaxaca,southern Mexico     

Grajales-Nishimura  José Manuel  Ramos-Arias  Mario Alfredo  Solari  Luigi  Murillo-Muñetón  Gustavo  Centeno-García  Elena  Schaaf  Peter  Torres-Vargas  Ricardo 《International Journal of Earth Sciences》2018,107(3):1005-1031

International Journal of Earth Sciences - The Juchatengo complex (JC) suite is located between the Proterozoic Oaxacan complex to the north and the Xolapa complex to the south, and was amalgamated...  相似文献   

Degradation and Detoxification of Chlorophenols in Continuous‐Flow Fixed‐Bed Aerobic Reactors     

Alfredo Gallego  Virginia L. Gemini  Susana L. Rossi  Carlos E. Gómez  Gustavo D. Bulus Rossini  Sonia E. Korol 《洁净——土壤、空气、水》2011,39(8):774-780

An indigenous bacterial strain of Delftia sp. capable of degrading 2,4‐dicholorophenol and an indigenous bacterial community that degrades 2,4,6‐trichlorophenol (TCP) were employed to inoculate continuous down‐flow fixed‐bed reactors. Continuous‐reactors were constructed from PVC employing hollow PVC cylinders as support material. Synthetic wastewater was prepared by dissolving the corresponding chlorophenol in non‐sterile groundwater. Biodegradation was evaluated by spectrophotometry, chloride release, GC, and microbial growth. Detoxification was evaluated by using Daphnia magna as test organism. Delftia sp. was able to remove an average of 95.6% of DCP. Efficiency in terms of chemical oxygen demand (COD) was of 88.9%. The indigenous bacterial community that degrades TCP reached an average efficiency of 96.5 and 91.6% in terms of compound and COD removal, respectively. In both cases stoichiometric removal of chloride and detoxification was achieved. When synthetic wastewater feed was cut off for 7 days, both reactors showed a fast recovery after inflow restarting, reaching average outlet concentration values within 36 h. The promising behavior of the microorganisms and the low cost of the reactors tested allow us to suggest their possible application to remediation processes.  相似文献   

Linking multi-temporal analysis and community consultation to evaluate the response to the impact of Hurricane Stan in coffee areas of Chiapas,Mexico     

Gustavo M. Cruz-Bello  Hallie Eakin  Helda Morales  Juan F. Barrera 《Natural Hazards》2011,58(1):103-116

This paper analyses the responses related to land use of coffee growers in Chiapas, Mexico to the impact of Hurricane Stan (October 2005). A multi-temporal analysis of the effect on land cover was performed through the combination of unsupervised classification of SPOT multispectral images and visual interpretation of panchromatic images (8 months previous to the hurricane, and 2, 14, and 40 months after the hurricane). The information provided by this geographic analysis was interpreted in light of information gathered though household surveys. Although the hurricane wrecked havoc across the region, the main impact in the study area was in the riparian zones where the extent of the loss experienced in terms of coffee harvest and soil was such that, even 14 months after the event, households with land in those areas were struggling to recover. Nevertheless, after 40 months, the zones that had suffered total soil loss began to support soil and vegetation, indicating the possibility of replanting coffee in those areas. Although the hurricane occurred when the coffee sector was particularly fragile as a result of the preceding several years of poor prices, the impact did not trigger extensive land use change. The surveys showed, however, that people are now more informed of the risk of living and farming on the river margins and are now performing soil conservation practices and planting trees to reduce risk.  相似文献   

Normalized algorithm for mapping and dating forest disturbances and regrowth for the United States     

Liming He  Jing M. Chen  Shaoliang Zhang  Gustavo Gomez  Yude Pan  Kevin McCullough  Richard Birdsey  Jeffrey G. Masek 《International Journal of Applied Earth Observation and Geoinformation》2011

Forest disturbances such as harvesting, wildfire and insect infestation are critical ecosystem processes affecting the carbon cycle. Because carbon dynamics are related to time since disturbance, forest stand age that can be used as a surrogate for major clear-cut/fire disturbance information has recently been recognized as an important input to forest carbon cycle models for improving prediction accuracy. In this study, forest disturbances in the USA for the period of ∼1990–2000 were mapped using 400+ pairs of re-sampled Landsat TM/ETM scenes in 500m resolution, which were provided by the Landsat Ecosystem Disturbance Adaptive Processing System project. The detected disturbances were then separated into two five-year age groups, facilitated by Forest Inventory and Analysis (FIA) data, which was used to calculate the area of forest regeneration for each county in the USA.  相似文献   

Persistence and long-term memories of daily maximum and minimum temperatures in southern South America     

Gustavo Naumann  Walter M. Vargas  Juan L. Minetti 《Theoretical and Applied Climatology》2011,105(3-4):341-355

The persistence and long-term memories in daily maximum and minimum temperature series during the instrumental period in southern South America were analysed. Here, we found a markedly seasonal pattern both for short- and long-term memories that can lead to enhanced predictability on intraseasonal timescales. In addition, well-defined spatial patterns of these properties were found in the region. Throughout the entire region, the strongest dependence was observed in autumn and early winter. In the Patagonia region only, the temperatures exhibited more memory during the spring. In general, these elements indicate that nonlinear interactions exist between the annual cycles of temperature and its anomalies. Knowledge of the spatiotemporal behaviour of these long-term memories can be used in the building of stochastic models that only use persistence. It is possible to propose two objective forecast models based on linear interactions associated with persistence and one that allows for the use of information from nonlinear interactions that are manifested in the form of forerunners.  相似文献   

Towards a comprehensive approach to parameter estimation in land surface parameterization schemes     

Rafael Rosolem  Hoshin V. Gupta  W. James Shuttleworth  Luis Gustavo Gonçalves de Gonçalves  Xubin Zeng 《水文研究》2013,27(14):2075-2097

In climate models, the land–atmosphere interactions are described numerically by land surface parameterization (LSP) schemes. The continuing improvement in realism in these schemes comes at the expense of the need to specify a large number of parameters that are either directly measured or estimated. Also, an emerging problem is whether the relationships used in LSPs are universal and globally applicable. One plausible approach to evaluate this is to first minimize uncertainty in model parameters by calibration. In this paper, we conduct a comprehensive analysis of some model diagnostics using a slightly modified version of the Simple Biosphere 3 model for a variety of biomes located mainly in the Amazon. First, the degree of influence of each individual parameter in simulating surface fluxes is identified. Next, we estimate parameters using a multi‐operator genetic algorithm applied in a multi‐objective context and evaluate simulations of energy and carbon fluxes against observations. Compared with the default parameter sets, these parameter estimates improve the partitioning of energy fluxes in forest and cropland sites and provide better simulations of daytime increases in assimilation of net carbon during the dry season at forest sites. Finally, a detailed assessment of the parameter estimation problem was performed by accounting for the decomposition of the mean squared error to the total model uncertainty. Analysis of the total prediction uncertainty reveals that the parameter adjustments significantly improve reproduction of the mean and variability of the flux time series at all sites and generally remove seasonality of the errors but do not improve dynamical properties. Our results demonstrate that error decomposition provides a meaningful and intuitive way to understand differences in model performance. To make further advancements in the knowledge of these models, we encourage the LSP community to adopt similar approaches in the future. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

Classification of seismic signals at Villarrica volcano (Chile) using neural networks and genetic algorithms     

Gloria Curilem  Jorge Vergara  Gustavo Fuentealba  Gonzalo Acuña  Max Chacón 《Journal of Volcanology and Geothermal Research》2009

Each volcano has its own unique seismic activity. The aim of this work is to construct a system able to classify seismic signals for the Villarrica volcano, one of the most active volcanoes in South America. Since seismic signals are the result of particular processes inside the volcano's structure, they can be used to forecast volcanic activity. This paper describes the different kinds of seismic signals recorded at the Villarrica volcano and their significance. Three kind of signals were considered as most representative of this volcano's activity: the long-period, the tremor, and the energetic tremor signals. A classifier is implemented to read the seismic registers at 30-second intervals, extract the most relevant features of each interval, and classify them into one of the three kinds of signals considered as most representative of this particular volcano. To do so, 1033 different kinds of 30-s signals were extracted and classified by a human expert. A feature extraction process was applied to obtain the main characteristics of each of them. This process was developed using criteria which have been shown by others to effectively classify seismic signals, based on the experience of a human expert. The classifier was implemented with a Multi-Layer Perceptron (MLP) artificial neural network whose architecture and training process were optimized by means of a genetic algorithm. This technique searched for the most adequate MLP configuration to improve the classification performance, optimizing the number of hidden neurons, the transfer functions of the neurons, and the training algorithm. The optimization process also performed a feature selection to reduce the number of signal features, optimizing the number of network inputs. The results show that the optimized classifier reaches more than 93% exactitude. identifying the signals of each kind. The amplitude of the signals is the most important feature for its classification, followed by its frequency content. The described methodology can be used to classify more seismic signals to improve the study of the activity of this volcano or to extend the study to other active volcanoes of the region.  相似文献