Forecast of lacustrine shale lithofacies types in continental rift basins based on machine learning: A case study from Dongying Sag, Jiyang Depression, Bohai Bay Basin, China

Lacustrine shale in continental rift basins is complex and features a variety of mineralogical compositions and microstructures. The lithofacies type of shale, mainly determined by mineralogical composition and microstructure, is the most critical factor controlling the quality of shale oil reservoirs. Conventional geophysical methods cannot accurately forecast lacustrine shale lithofacies types, thus restricting the progress of shale oil exploration and development. Considering the lacustrine shale in the upper Es4 member of the Dongying Sag in the Jiyang Depression, Bohai Bay Basin, China, as the research object, the lithofacies type was forecast based on two machine learning methods: support vector machine (SVM) and extreme gradient boosting (XGBoost). To improve the forecast accuracy, we applied the following approaches: first, using core and thin section analyses of consecutively cored wells, the lithofacies were finely reclassified into 22 types according to mineralogical composition and microstructure, and the vertical change of lithofacies types was obtained. Second, in addition to commonly used well logging data, paleoenvironment parameter data (Rb/Sr ratio, paleoclimate parameter; Sr %, paleosalinity parameter; Ti %, paleoprovenance parameter; Fe/Mn ratio, paleo-water depth parameter; P/Ti ratio, paleoproductivity parameter) were applied to the forecast. Third, two sample extraction modes, namely, curve shape-to-points and point-to-point, were used in the machine learning process. Finally, the lithofacies type forecast was carried out under six different conditions. In the condition of selecting the curved shape-to-point sample extraction mode and inputting both well logging and paleoenvironment parameter data, the SVM method achieved the highest average forecast accuracy for all lithofacies types, reaching 68%, as well as the highest average forecast accuracy for favorable lithofacies types at 98%. The forecast accuracy for all lithofacies types improved by 7%–28% by using both well logging and paleoenvironment parameter data rather than using one or the other, and was 7%–8% higher by using the curve shape-to-point sample extraction mode compared to the point-to-point sample extraction mode. In addition, the learning sample quantity and data value overlap of different lithofacies types affected the forecast accuracy. The results of our study confirm that machine learning is an effective solution to forecast lacustrine shale lithofacies. When adopting machine learning methods, increasing the learning sample quantity (>45 groups), selecting the curve shape-to-point sample extraction mode, and using both well logging and paleoenvironment parameter data are effective ways to improve the forecast accuracy of lacustrine shale lithofacies types. The method and results of this study provide guidance to accurately forecast the lacustrine shale lithofacies types in new shale oil wells and will promote the harvest of lacustrine shale oil globally

How Robust is Google's Bard to Adversarial Image Attacks?

Multimodal Large Language Models (MLLMs) that integrate text and other modalities (especially vision) have achieved unprecedented performance in various multimodal tasks. However, due to the unsolved adversarial robustness problem of vision models, MLLMs can have more severe safety and security risks by introducing the vision inputs. In this work, we study the adversarial robustness of Google's Bard, a competitive chatbot to ChatGPT that released its multimodal capability recently, to better understand the vulnerabilities of commercial MLLMs. By attacking white-box surrogate vision encoders or MLLMs, the generated adversarial examples can mislead Bard to output wrong image descriptions with a 22% success rate based solely on the transferability. We show that the adversarial examples can also attack other MLLMs, e.g., a 26% attack success rate against Bing Chat and a 86% attack success rate against ERNIE bot. Moreover, we identify two defense mechanisms of Bard, including face detection and toxicity detection of images. We design corresponding attacks to evade these defenses, demonstrating that the current defenses of Bard are also vulnerable. We hope this work can deepen our understanding on the robustness of MLLMs and facilitate future research on defenses. Our code is available at https://github.com/thu-ml/Attack-Bard. Update: GPT-4V is available at October 2023. We further evaluate its robustness under the same set of adversarial examples, achieving a 45% attack success rate.Comment: Technical repor

Models Analyses for Allelopathic Effects of Chicory at Equivalent Coupling of Nitrogen Supply and pH Level on F. arundinacea, T. repens and M. sativa

Alllelopathic potential of chicory was investigated by evaluating its effect on seed germination, soluble sugar, malondialdehyde (MDA) and the chlorophyll content of three target plants species (Festuca arundinacea, Trifolium repens and Medicago sativa). The secretion of allelochemicals was regulated by keeping the donor plant (chicory) separate from the three target plant species and using different pH and nitrogen levels. Leachates from donor pots with different pH levels and nitrogen concentrations continuously irrigated the target pots containing the seedlings. The allelopathic effects of the chicory at equivalent coupling of nitrogen supply and pH level on the three target plants species were explored via models analyses. The results suggested a positive effect of nitrogen supply and pH level on allelochemical secretion from chicory plants. The nitrogen supply and pH level were located at a rectangular area defined by 149 to 168 mg/l nitrogen supply combining 4.95 to 7.0 pH value and point located at nitrogen supply 177 mg/l, pH 6.33 when they were in equivalent coupling effects; whereas the inhibitory effects of equivalent coupling nitrogen supply and pH level were located at rectangular area defined by 125 to 131 mg/l nitrogen supply combining 6.71 to 6.88 pH value and two points respectively located at nitrogen supply 180 mg/l with pH 6.38 and nitrogen supply 166 mg/l with pH 7.59. Aqueous extracts of chicory fleshy roots and leaves accompanied by treatment at different sand pH values and nitrogen concentrations influenced germination, seedling growth, soluble sugar, MDA and chlorophyll of F. arundinacea, T. repens and M. sativa. Additionally, we determined the phenolics contents of root and leaf aqueous extracts, which were 0.104% and 0.044% on average, respectively

Self-Calibration Spherical Video Stabilization Based on Gyroscope

With the development of handheld video capturing devices, video stabilization becomes increasingly important. The gyroscope-based video stabilization methods perform promising ability, since they can return more reliable three-dimensional (3D) camera rotation estimation, especially when there are many moving objects in scenes or there are serious motion blur or illumination changes. However, the gyroscope-based methods depend on the camera intrinsic parameters to execute video stabilization. Therefore, a self-calibrated spherical video stabilization method was proposed. It builds a virtual sphere, of which the spherical radius is calibrated automatically, and then projects each frame of the video to the sphere. Through the inverse rotation of the spherical image according to the rotation jitter component, the dependence on the camera intrinsic parameters is relaxed. The experimental results showed that the proposed method does not need to calibrate the camera and it can suppress the camera jitter by binding the gyroscope on the camera. Moreover, compared with other state-of-the-art methods, the proposed method can improve the peak signal-to-noise ratio, the structural similarity metric, the cropping ratio, the distortion score, and the stability score

Controlling factors of matrix acidizing potential of low permeability clastic reservoir in faulted lacustrine basin

Based on constant rate mercury injection experiment, casting thin section identification, scanning electron microscope observation, clay mineral X-ray and rock specific surface area analysis, the controlling factors of matrix acidizing potential of low-permeability sandstone reservoir in fault depression lacustrine basin were determined from three aspects: pore filling, throat filling and pore-throat combination characteristics. It is concluded that provenance controls the plane partition of reservoir pore fillings. Burial depth controls the longitudinal zoning of key filling material in reservoir throat. The difference of rock structure in sedimentary facies - microfacies controlling zone leads to the change of pore-throat assemblage pattern. The matrix acidizing scheme of low permeability sandstone reservoir in fault depression basin can be formulated according to the law of “provenance zoning, buried depth zoning and being controlled by microfacies in zone”, and the implementation scheme of pre-acid, main acid and post-acid can be put forward respectively. This method can effectively promote the integration process of exploration and development of low permeability clastic reservoir in mature exploration area

Underground Pipeline Data Matching Considering Multiple Spatial Similarities

Integrated and professional underground pipeline data are two forms of pipeline.Integrated underground pipeline data is accurate and general, while professional underground pipeline data expresses and contains detailed attribute information.Taking the data of natural gas pipeline as an example, this paper calculates structural similarity measured by the distribution pattern of pipelines that pipeline-point connects with, semantic similarity presented by the names and attributes of the pipeline-point ontology concept, and shape similarity characterized by the shape of arcs between two pipeline-points. The matching of pipe points is realized with the method of support vector machine classification algorithm and unique-matching principle combined with these spatial similarity. Test results show the matching of pipe points is well solved by the proposed algorithm

A Parallax Image Mosaic Method for Low Altitude Aerial Photography with Artifact and Distortion Suppression

In this paper, we propose an aerial images stitching method based on an as-projective-as-possible (APAP) algorithm, aiming at the problem artifacts, distortions, or stitching failure due to fewer feature points for multispectral aerial image with certain parallax. Our method incorporates accelerated nonlinear diffusion algorithm (AKAZE) into APAP algorithm. First, we use the fast and stable AKAZE to extract the feature points of aerial images, and then, based on the registration model of the APAP algorithm, we add line protection constraints, global similarity constraints, and local similarity constraints to protect the image structure information, to produce a panorama. Experimental results on several datasets demonstrate that proposed method is effective when dealing with multispectral aerial images. Our method can suppress artifacts, distortions, and reduce incomplete splicing. Compared with state-of-the-art image stitching methods, including APAP and adaptive as-natural-as-possible image stitching (AANAP), and two of the most popular UAV image stitching tools, Pix4D and OpenDroneMap (ODM), our method achieves them both quantitatively and qualitatively

Investigation of electronic, dielectric, and plasmonic properties of two-dimensional electride Ba

Ba4Al5 is an electride in which excess anion electrons are confined in the two-dimensional interlayer region. Here, we carry out a systematical study on the electronic, optical, and plasmonic properties of Ba4Al5 using the first-principles calculations. It is found that the metallic Ba4Al5 has a relatively low cleavage energy (~ 0.77 J/m2), suggesting a weak interlayer interaction and the easiness of exfoliation. Importantly, Ba4Al5 possesses a low work function on the (001) surface and exhibit excellent optical properties, such as high light absorption coefficient with weak optical anisotropy that becomes stronger when decreasing the thickness. It is further found that Ba4Al5 is also a suitable plasmonic material which can be used in the near-infrared frequency range