Physics-informed neural network for inverse modeling of natural-state geothermal systems

Predicting the temperature, pressure, and permeability at depth is crucial for understanding natural-state geothermal systems. As direct observations of these quantities are limited to well locations, a reliable method-ology that predicts the spatial distribution of the quantities from well observations is required. In this study, we developed a physics-informed neural network (PINN), which constrains predictions to satisfy conservation of mass and energy, for predicting spatial distributions of temperature, pressure, and permeability of natural-state hydrothermal systems. We assessed the characteristics of the proposed method by applying it to 2D synthetic models of geothermal systems. Our results showed that the PINN outperformed the conventional neural network in terms of prediction accuracy. Among the PINN-predicted quantities, the errors in the predicted temperatures in the unexplored regions were significantly reduced. Furthermore, we confirmed that the predictions decreased the loss of the conservation laws. Thus, our PINN approach guarantees physical plausibility, which has been impossible using existing machine learning approaches. As permeability investigations in geothermal wells are often limited, we also demonstrate that the resistivity model obtained using the magnetotelluric method is effective in supplementing permeability observations and improving its prediction accuracy. This study demonstrated for the first time the usefulness of the PINN to a geothermal energy problem

More is simpler : effectively and efficiently assessing node-pair similarities based on hyperlinks

Similarity assessment is one of the core tasks in hyperlink analysis. Recently, with the proliferation of applications, e.g., web search and collaborative filtering, SimRank has been a well-studied measure of similarity between two nodes in a graph. It recursively follows the philosophy that "two nodes are similar if they are referenced (have incoming edges) from similar nodes", which can be viewed as an aggregation of similarities based on incoming paths. Despite its popularity, SimRank has an undesirable property, i.e., "zero-similarity": It only accommodates paths with equal length from a common "center" node. Thus, a large portion of other paths are fully ignored. This paper attempts to remedy this issue. (1) We propose and rigorously justify SimRank*, a revised version of SimRank, which resolves such counter-intuitive "zero-similarity" issues while inheriting merits of the basic SimRank philosophy. (2) We show that the series form of SimRank* can be reduced to a fairly succinct and elegant closed form, which looks even simpler than SimRank, yet enriches semantics without suffering from increased computational cost. This leads to a fixed-point iterative paradigm of SimRank* in O(Knm) time on a graph of n nodes and m edges for K iterations, which is comparable to SimRank. (3) To further optimize SimRank* computation, we leverage a novel clustering strategy via edge concentration. Due to its NP-hardness, we devise an efficient and effective heuristic to speed up SimRank* computation to O(Knm) time, where m is generally much smaller than m. (4) Using real and synthetic data, we empirically verify the rich semantics of SimRank*, and demonstrate its high computation efficiency

Fast incremental SimRank on link-evolving graphs

SimRank is an arresting measure of node-pair similarity based on hyperlinks. It iteratively follows the concept that 2 nodes are similar if they are referenced by similar nodes. Real graphs are often large, and links constantly evolve with small changes over time. This paper considers fast incremental computations of SimRank on link-evolving graphs. The prior approach [12] to this issue factorizes the graph via a singular value decomposition (SVD) first, and then incrementally maintains this factorization for link updates at the expense of exactness. Consequently, all node-pair similarities are estimated in O(r4n2) time on a graph of n nodes, where r is the target rank of the low-rank approximation, which is not negligibly small in practice. In this paper, we propose a novel fast incremental paradigm. (1) We characterize the SimRank update matrix ΔS, in response to every link update, via a rank-one Sylvester matrix equation. By virtue of this, we devise a fast incremental algorithm computing similarities of n2 node-pairs in O(Kn2) time for K iterations. (2) We also propose an effective pruning technique capturing the “affected areas” of ΔS to skip unnecessary computations, without loss of exactness. This can further accelerate the incremental SimRank computation to O(K(nd+|AFF|)) time, where d is the average in-degree of the old graph, and |AFF| (≤ n2) is the size of “affected areas” in ΔS, and in practice, |AFF| ≪ n2. Our empirical evaluations verify that our algorithm (a) outperforms the best known link-update algorithm [12], and (b) runs much faster than its batch counterpart when link updates are small

Three-dimensional stress state above and below the plate boundary fault after the 2011 Mw 9.0 Tohoku earthquake

東北地方太平洋沖地震を引き起こしたプレート境界断層より以深の応力状態を初めて決定 --海洋底掘削で採取されたコア試料の非弾性ひずみ解析からのアプローチ--. 京都大学プレスリリース. 2022-11-11.Finding faults deeply stressful: First investigation of stress state below plate boundary fault of Tohoku earthquake. 京都大学プレスリリース. 2022-12-09.The Integrated Ocean Drilling Program conducted Expedition 343 and 343T, named the Japan Trench Fast Drilling Project (JFAST), to drill through the plate boundary fault that ruptured during the 2011 Mw 9.0 Tohoku earthquake in the area with the largest fault slip displacement near the Japan trench. Analyses of breakouts observed from borehole C0019B produced postearthquake stress states above the plate boundary fault between the subducting Pacific plate and overriding North American plate. To supplement the lack of stress data below the rupture zone of the earthquake, we conducted core-based three-dimensional stress measurements by the anelastic strain recovery (ASR) method using four whole-round core samples of sediments, of which three samples were located above, but one sample was located below the plate boundary fault in borehole C0019E. As a result of the stress measurements, the postearthquake three-dimensional stress magnitudes at ∼802 and ∼828 meters below seafloor (mbsf) across the plate boundary fault at ∼820 mbsf reveal a normal faulting stress regime. The differences between the three-dimensional intermediate principal stress and the minimum principal stress at the two depths are less than 1 MPa, suggesting a complete release of horizontal tectonic stresses that accumulated before the earthquake. In addition, the maximum horizontal stress S[Hmax] azimuth N115°E at ∼828 mbsf below the plate boundary fault from ASR measurements shows consistency with the S[Hmax] azimuth N139 ± 23°E (mean ± standard deviation) at ∼550–810 mbsf from breakout analyses above the fault. Taken together with the similar stress magnitudes at ∼802 and ∼828 mbsf, we interpret that the postearthquake stress states are almost the same in the sediments above and below the plate boundary fault. In other words, the stress state in terms of both orientation and magnitude is continuous across the fault. At a shallower depth of ∼177 mbsf in the slope sediments, the ASR stress data reveal a “stress state at rest”, which is likely free from tectonic effects of plate subduction, suggesting that the stress state was reset by the great coseismic displacement of ∼50 m slipped during the Tohoku earthquake

Measurement of thermal conductivities of drill cuttings and quantification of the contribution of thermal conduction to the temperature log of the Hachimantai geothermal field, Japan

This study proposed and evaluated a method of measuring the thermal conductivity (TC) of drill cuttings from several igneous and pyroclastic rocks using the transient plane source principle, which allows quick and reliable measurements. The estimated bulk TCs of rocks were within an error of <10%, and suitable models were found. Measurements were applied to drill cuttings obtained along a well in the Hachimantai geothermal field, Japan, and TCs were obtained at ∼25 m intervals to a depth of 1700 m. Our analysis of the temperature profile using estimated TCs suggest the possible presence of fluid-flow zones in the well

IRWR: Incremental Random Walk with Restart

ABSTRACT Random Walk with Restart (RWR) has become an appealing measure of node proximities in emerging applications e.g., recommender systems and automatic image captioning. In practice, a real graph is typically large, and is frequently updated with small changes. It is often cost-inhibitive to recompute proximities from scratch via batch algorithms when the graph is updated. This paper focuses on the incremental computations of RWR in a dynamic graph, whose edges often change over time. The prior attempt of RWR [1] deploys k-dash to find top-k highest proximity nodes for a given query, which involves a strategy to incrementally estimate upper proximity bounds. However, due to its aim to prune needless calculation, such an incremental strategy is approximate: in O(1) time for each node. The main contribution of this paper is to devise an exact and fast incremental algorithm of RWR for edge updates. Our solution, IRWR , can incrementally compute any node proximity in O(1) time for each edge update without loss of exactness. The empirical evaluations show the high efficiency and exactness of IRWR for computing proximities on dynamic networks against its batch counterparts

An Ancient >200 m Cumulative Normal Faulting Displacement Along the Futagawa Fault Dextrally Ruptured During the 2016 Kumamoto, Japan, Earthquake Identified by a Multiborehole Drilling Program

【研究成果】布田川断層での200 mを超える落差の発見 --火山活動と関係した断層運動の”縦ずれ”から”横ずれ”への変化--. 京都大学プレスリリース. 2022-01-28.The Mw 7.0 mainshock of the 2016 Kumamoto earthquake sequence was triggered by dextral rupture of the Futagawa fault within the Aso volcanic region, Southwestern Japan. To reproduce its faulting patterns and to reveal the geological and geophysical characteristics of the fault and surrounding lithological units, we report the results of a multiple-borehole drilling program penetrating the Futagawa fault zone. By combining core descriptions with geophysical logs, we identified >200 m of normal faulting displacement along the currently dextral strike-slip Futagawa fault. Considering previous kinematic and chronological studies of the fault, we interpret that the Futagawa fault dominantly slipped as a normal fault in a short period (∼300–87 ka) before switching to its current transtensional (dominant strike-slip) regime ∼87 ka caused by a local change in the stress field associated with the termination of the Aso caldera-forming eruptions. In the main borehole, three damage/slip zones were penetrated at depths of ∼354, 461, and 576 m. The 461 damage zone was identified as ∼45 m in vertical thickness and thicker than the other damage zones (∼3–6 m vertically) and was characterized by high fracture density and the presence of strike-slip slickenlines. Depth profiles of physical properties revealed different patterns near the three damage zones; both the resistivity and the P-wave velocity showed stronger deterioration at the 461 damage zone than the others. Based on these geological and geophysical observations, we suggest that the 461 damage zone is the primary candidate for seismogenic faulting during the 2016 Kumamoto earthquake mainshock

Strain Softening of Siltstones in Consolidation Process

Strain softening is the mechanical behavior of soil and rock materials and is important in understanding soft rock foundation. To investigate the mechanical behavior of siltstone, a sedimentary soft rock, consolidation tests using constant-strain rate loading were conducted using the consolidation ring to constrain lateral deformation. Using Quaternary siltstones distributed in the Boso Peninsula, central Japan as specimens, strain softening in the consolidation process was confirmed in some formations using two test machines at Kyoto University and Nagoya Institute of Technology. Just before the yielding, stress decreased suddenly at increasing strain. The stress at the time of the softening differed even for specimens taken from the same formation. Furthermore, micro-focus X-ray CT images taken before and after the tests indicated that the specimens had no macro cracks inside. This suggests that strain softening is not due to brittle failure in local areas but due to the softening of the framework structure of the siltstone itself

TDCMR: Triplet-Based Deep Cross-Modal Retrieval for geo-multimedia data

Mass multimedia data with geographical information (geo-multimedia) are collected and stored on the Internet due to the wide application of location-based services (LBS). How to find the high-level semantic relationship between geo-multimedia data and construct efficient index is crucial for large-scale geo-multimedia retrieval. To combat this challenge, the paper proposes a deep cross-modal hashing framework for geo-multimedia retrieval, termed as Triplet-based Deep Cross-Modal Retrieval (TDCMR), which utilizes deep neural network and an enhanced triplet constraint to capture high-level semantics. Besides, a novel hybrid index, called TH-Quadtree, is developed by combining cross-modal binary hash codes and quadtree to support high-performance search. Extensive experiments are conducted on three common used benchmarks, and the results show the superior performance of the proposed method