The temperature distribution at depth is a key variable when assessing the potential of a supercritical geothermal resource as well as a conventional geothermal resource. Data-driven estimation by a machine-learning approach is a promising way to estimate temperature distributions at depth in geothermal fields. In this study, we developed two methodologies—one based on Bayesian estimation and the other on neural networks—to estimate temperature distributions in geothermal fields. These methodologies can be used to supplement existing temperature logs, by estimating temperature distributions in unexplored regions of the subsurface, based on electrical resistivity data, observed geological/mineralogical boundaries, and microseismic observations. We evaluated the accuracy and characteristics of these methodologies using a numerical model of the Kakkonda geothermal field, Japan, where a temperature above 500 °C was observed below a depth of about 3.7 km. When using geological and geophysical knowledge as prior information for the machine learning methods, the results demonstrate that the approaches can provide subsurface temperature estimates that are consistent with the temperature distribution given by the numerical model. Using a numerical model as a benchmark helps to understand the characteristics of the machine learning approaches and may help to identify ways of improving these methods.
Point-positioning GPS-based wave measurements were conducted by deep ocean (over 5,000 m) surface buoys moored in the North West Pacific Ocean in 2009, 2012, and 2013. The observed surface elevation bears statistical characteristics of Gaussian, spectrally narrow ocean waves. The tail of the averaged spectrum follows the frequency to the power of ?4 slope, and the significant wave height and period satisfies the Toba’s 3/2 law. The observations compare well with a numerical wave hindcast. Two large freak waves exceeding 13 m in height were observed in October 2009 and three extreme waves around 20 m in height were observed in October 2012 and in January 2013. These extreme events are associated with passages of a typhoon and a mid-latitude cyclone. Horizontal movement of the buoy revealed that the orbital motion of the waves at the peak of the wave group mostly exceed the weakly nonlinear estimate. For some cases, the orbital velocity exceeded the group velocity, which might indicate a breaking event but is not conclusive yet. 相似文献
A frequency and spatial domain decomposition method (FSDD) for operational modal analysis (OMA) is presented in this paper, which is an extension of the complex mode indicator function (CMIF) method for experimental modal analysis (EMA). The theoretical background of the FSDD method is clarified, Singular value decomposition is adopted to separate the signal space from the noise space. Finally, an enhanced power spectrum density (PSD) is proposed to obtain more accurate modal parameters by curve fitting in the frequency domain. Moreover, a simulation case and an application case are used to validate this method. 相似文献
We investigated the feasibility of the ensemble Kalman filter (EnKF) to reproduce oceanic conditions south of Japan. We have
adopted the local ensemble transformation Kalman filter algorithm based on 20 members’ ensemble simulations of the parallelized
Princeton Ocean Model (the Stony Brook Parallel Ocean Model) with horizontal resolution of 1/36°. By assimilating satellite
sea surface height anomaly, satellite sea surface temperature, and in situ temperature and salinity profiles, we reproduced
the Kuroshio variation south of Japan for the period from 8 to 28 February 2010. EnKF successfully reproduced the Kuroshio
path positions and the water mass property of the Kuroshio waters as observed. It also detected the variation of the steep
thermohaline front in the Kii Channel due to the intrusion of the Kuroshio water based on the observation, suggesting efficiency
of EnKF for detection of open and coastal seas interactions with highly complicated spatiotemporal variability. 相似文献
We investigated the size fraction and pigment-derived class compositions of phytoplankton within the euphotic zone of the Antarctic marginal ice zone between 63.3°S and 66.5°S along the 140°E meridian on two consecutive cruises in the late austral summer and early austral autumn of 2003. We observed significant temporal and spatial variations in phytoplankton size and taxonomic composition, although chlorophyll a concentrations were generally below 1 μg l−1 during both periods. Microphytoplankton (>20 μm), mainly diatoms, were prominent in the euphotic zone in the southernmost area around 66.5°S during late summer. In the rest of the study area during both cruises, the phytoplankton community was dominated by pico- and nano-sized populations (<20 μm) throughout the euphotic zone. The small-size populations mostly consisted of diatoms and haptophytes, although chlorophytes were dominant in extremely cold water (−1.5°C) below the overlying warm water around 65.5°S during late summer. From late summer to early autumn, chlorophytes declined in abundance, probably due to increasing temperature within the euphotic zone (−1 to 0°C). These pico- and nano-phytoplankton-dominated populations were often accompanied by relatively high concentrations of ammonium, suggesting the active regeneration of nutrients within the small-size plankton community. 相似文献
The signal measured by heave–pitch–roll directional wave buoys yields the first four coefficients of a Fourier series. Data adaptive methods must be employed to estimate a directional wave spectrum. Marine X-band radars (MRs) have the advantage over buoys that they can measure “model-free” two-dimensional (2D) wave spectra. This study presents the first comprehensive validation of MR-derived multi-directional wave characteristics. It is based on wave data from the 2010 Impact of Typhoons on the Ocean in the Pacific (ITOP) experiment in the Philippine Sea, namely MR measurements from R/V Roger Revelle, Extreme Air–Sea Interaction (EASI) buoy measurements, as well as WAVEWATCH-III (WW3) modeling results. Buoy measurements of mean direction and spreading as function of frequency, which do not require data adaptive methods, are used to validate the WW3 wave spectra. An advanced MR wave retrieval technique is introduced that addresses various shortcomings of existing methods. Spectral partitioning techniques, applied to MR and WW3 results, reveal that multimodal seas are frequently present. Both data sets are in excellent agreement, tracking the evolution of up to 4 simultaneous wave systems over extended time periods. This study demonstrates MR’s and WW3’s strength at measuring and predicting 2D wave spectra in swell-dominated seas. 相似文献
日本原子能机构(Japan Atomic Energy Agency)提出了一种方法,即通过地表原地应力测量所得的有限数据精确估算任意一点的实际原地应力状态分布.我们假定实际地应力是由上覆岩层压力和板块构造力的综合作用形成的,并建立了两种模型:三维有限元模型和边界元模型,模型考虑了地质情况的不均匀性,如岩石类型的变化和... 相似文献