Oilfield analogy and productivity prediction based on machine learning: Field cases in PL oilfield, China

In the early time of oilfield development, insufficient production data and unclear understanding of oil production presented a challenge to reservoir engineers in devising effective development plans. To address this challenge, this study proposes a method using data mining technology to search for similar oil fields and predict well productivity. A query system of 135 analogy parameters is established based on geological and reservoir engineering research, and the weight values of these parameters are calculated using a data algorithm to establish an analogy system. The fuzzy matter-element algorithm is then used to calculate the similarity between oil fields, with fields having similarity greater than 70% identified as similar oil fields. Using similar oil fields as sample data, 8 important factors affecting well productivity are identified using the Pearson coefficient and mean decrease impurity(MDI) method. To establish productivity prediction models, linear regression(LR), random forest regression(RF), support vector regression(SVR), backpropagation(BP), extreme gradient boosting(XGBoost), and light gradient boosting machine(Light GBM) algorithms are used. Their performance is evaluated using the coefficient of determination(R^(2)), explained variance score(EV), mean squared error(MSE), and mean absolute error(MAE) metrics. The Light GBM model is selected to predict the productivity of 30 wells in the PL field with an average error of only 6.31%, which significantly improves the accuracy of the productivity prediction and meets the application requirements in the field. Finally, a software platform integrating data query,oil field analogy, productivity prediction, and knowledge base is established to identify patterns in massive reservoir development data and provide valuable technical references for new reservoir development.

Progress on Transition Metal Ions Dissolution Suppression Strategies in Prussian Blue Analogs for Aqueous Sodium-/Potassium-Ion Batteries

Aqueous sodium-ion batteries(ASIBs)and aqueous potassium-ion batteries(APIBs)present significant potential for large-scale energy storage due to their cost-effectiveness,safety,and environmental compatibility.Nonetheless,the intricate energy storage mechanisms in aqueous electrolytes place stringent require-ments on the host materials.Prussian blue analogs(PBAs),with their open three-dimensional framework and facile synthesis,stand out as leading candidates for aqueous energy storage.However,PBAs possess a swift capacity fade and limited cycle longevity,for their structural integrity is compromised by the pronounced dis-solution of transition metal(TM)ions in the aqueous milieu.This manuscript provides an exhaustive review of the recent advancements concerning PBAs in ASIBs and APIBs.The dissolution mechanisms of TM ions in PBAs,informed by their structural attributes and redox processes,are thoroughly examined.Moreover,this study delves into innovative design tactics to alleviate the dissolution issue of TM ions.In conclusion,the paper consolidates various strategies for suppressing the dissolution of TM ions in PBAs and posits avenues for prospective exploration of high-safety aqueous sodium-/potassium-ion batteries.

The Analogy between the Immune System and Human Life

The immune system operates as a complex organization with distinct roles and functions. Excitingly we recognized the similarities between the cellular dynamics of the immune system and our lives, activities, and behaviors. Observing the immune system can guide how to respond to various daily situations, including when to react, tolerate, or ignore. Recognizing this analogy between our lives and the immune system should motivate us to adopt a wisdom-based approach when investigating the mechanisms and future discoveries related to this system and to deepen our understanding of this complex system with newfound respect. In this context, the present review examines several integral biological processes of the immune system by drawing parallels between them and human life, activities, and behaviors to learn how we must behave based on the insights offered by this complex organization. The literature search was conducted in international databases such as PubMed/MEDLINE and Google Scholar search engine using English equivalent keywords from 1998 up to April 2023. The search strategy used the following subject heading terms: Immune system, analogy, human life, cellular dynamics, memory, tolerance, and ignorance. In conclusion, the immune system is a complex organization comprising various cells interacting within specific sites and networks, communicating, drawing experiences, and learning how to tolerate certain conditions that make it share certain similarities with human life.

Discovery of a geomorphological analog to Martian araneiforms in the Qaidam Basin, Tibetan Plateau

Araneiforms are spider-like ground patterns that are widespread in the southern polar regions of Mars.A gas erosion process driven by the seasonal sublimation of CO_(2) ice was proposed as an explanation for their formation,which cannot occur on Earth due to the high climatic temperature.In this study,we propose an alternative mechanism that attrib-utes the araneiform formation to the erosion of upwelling salt water from the subsurface,relying on the identification of the first terrestrial analog found in a playa of the Qaidam Basin on the northern Tibetan Plateau.Morphological analysis indicates that the structures in the Qaidam Basin have fractal features comparable to araneiforms on Mars.A numerical model is developed to investigate the araneiform formation driven by the water-diffusion mechanism.The simulation res-ults indicate that the water-diffusion process,under varying ground conditions,may be responsible for the diverse aranei-form morphologies observed on both Earth and Mars.Our numerical simulations also demonstrate that the orientations of the saltwater diffusion networks are controlled by pre-existing polygonal cracks,which is consistent with observations of araneiforms on Mars and Earth.Our study thus suggests that a saltwater-related origin of the araneiform is possible and has significant implications for water searches on Mars.

An analogical study of wave equations,physical quantities,conservation and reciprocity equations between electromagnetic and elastic waves

This paper presents an analogical study between electromagnetic and elastic wave fields,with a one-to-one correspondence principle established regarding the basic wave equations,the physical quantities and the differential operations.Using the electromagnetic-to-elastic substitution,the analogous relations of the conservation laws of energy and momentum are investigated between these two physical fields.Moreover,the energy-based and momentum-based reciprocity theorems for an elastic wave are also derived in the time-harmonic state,which describe the interaction between two elastic wave systems from the perspectives of energy and momentum,respectively.The theoretical results obtained in this analysis can not only improve our understanding of the similarities of these two linear systems,but also find potential applications in relevant fields such as medical imaging,non-destructive evaluation,acoustic microscopy,seismology and exploratory geophysics.

Tackling the Existential Threats from Quantum Computers and AI

Although AI and quantum computing (QC) are fast emerging as key enablers of the future Internet, experts believe they pose an existential threat to humanity. Responding to the frenzied release of ChatGPT/GPT-4, thousands of alarmed tech leaders recently signed an open letter to pause AI research to prepare for the catastrophic threats to humanity from uncontrolled AGI (Artificial General Intelligence). Perceived as an “epistemological nightmare”, AGI is believed to be on the anvil with GPT-5. Two computing rules appear responsible for these risks. 1) Mandatory third-party permissions that allow computers to run applications at the expense of introducing vulnerabilities. 2) The Halting Problem of Turing-complete AI programming languages potentially renders AGI unstoppable. The double whammy of these inherent weaknesses remains invincible under the legacy systems. A recent cybersecurity breakthrough shows that banning all permissions reduces the computer attack surface to zero, delivering a new zero vulnerability computing (ZVC) paradigm. Deploying ZVC and blockchain, this paper formulates and supports a hypothesis: “Safe, secure, ethical, controllable AGI/QC is possible by conquering the two unassailable rules of computability.” Pursued by a European consortium, testing/proving the proposed hypothesis will have a groundbreaking impact on the future digital infrastructure when AGI/QC starts powering the 75 billion internet devices by 2025.

Experimental and computational optimization of Prussian blue analogues as high-performance cathodes for sodium-ion batteries:A review

In this review,we discuss the electrochemical properties of Prussian blue(PB)for Na^(+)storage by combining structural engineering and electrolyte modifications.We integrated experimental data and density functional theory(DFT)in sodium-ion battery(SIB)research to refine the atomic arrangements and crystal lattices and introduce substitutions and dopants.These changes affect the lattice stability,intercalation,electronic and ionic conductivities,and electrochemical performance.We unraveled the intricate structure-electrochemical behavior relationship by combining experimental data with computational models,including first-principles calculations.This holistic approach identified techniques for optimizing PB and Prussian blue analog(PBA)structu ral properties for SIBs.We also discuss the tuning of electrolytes by systematically adjusting their composition,concentration,and additives using a combination of molecular dynamics(MD)simulations and DFT computations.Our review offers a comprehensive assessment of strategies for enhancing the electrochemical properties of PB and PBAs through structural engineering and electrolyte modifications,combining experimental insights with advanced computational simulations,and paving the way for next-generation energy storage systems.

Investigation on Analog and Digital Modulations Recognition Using Machine Learning Algorithms

In the field of radiocommunication, modulation type identification is one of the most important characteristics in signal processing. This study aims to implement a modulation recognition system on two approaches to machine learning techniques, the K-Nearest Neighbors (KNN) and Artificial Neural Networks (ANN). From a statistical and spectral analysis of signals, nine key differentiation features are extracted and used as input vectors for each trained model. The feature extraction is performed by using the Hilbert transform, the forward and inverse Fourier transforms. The experiments with the AMC Master dataset classify ten (10) types of analog and digital modulations. AM_DSB_FC, AM_DSB_SC, AM_USB, AM_LSB, FM, MPSK, 2PSK, MASK, 2ASK, MQAM are put forward in this article. For the simulation of the chosen model, signals are polluted by the Additive White Gaussian Noise (AWGN). The simulation results show that the best identification rate is the MLP neuronal method with 90.5% of accuracy after 10 dB signal-to-noise ratio value, with a shift of more than 15% from the k-nearest neighbors’ algorithm.

An Adaptive Control Strategy for Energy Storage Interface Converter Based on Analogous Virtual Synchronous Generator

In the DC microgrid,the lack of inertia and damping in power electronic converters results in poor stability of DC bus voltage and low inertia of the DC microgrid during fluctuations in load and photovoltaic power.To address this issue,the application of a virtual synchronous generator(VSG)in grid-connected inverters control is referenced and proposes a control strategy called the analogous virtual synchronous generator(AVSG)control strategy for the interface DC/DC converter of the battery in the microgrid.Besides,a flexible parameter adaptive control method is introduced to further enhance the inertial behavior of the AVSG control.Firstly,a theoretical analysis is conducted on the various components of the DC microgrid,the structure of analogous virtual synchronous generator,and the control structure’s main parameters related to the DC microgrid’s inertial behavior.Secondly,the voltage change rate tracking coefficient is introduced to adjust the change of the virtual capacitance and damping coefficient flexibility,which further strengthens the inertia trend of the DC microgrid.Additionally,a small-signal modeling approach is used to analyze the approximate range of the AVSG’s main parameters ensuring system stability.Finally,conduct a simulation analysis by building the model of the DC microgrid system with photovoltaic(PV)and battery energy storage(BES)in MATLAB/Simulink.Simulation results from different scenarios have verified that the AVSG control introduces fixed inertia and damping into the droop control of the battery,resulting in a certain level of inertia enhancement.Furthermore,the additional adaptive control strategy built upon the AVSG control provides better and flexible inertial support for the DC microgrid,further enhances the stability of the DC bus voltage,and has a more positive impact on the battery performance.

Optimal Stack Generation for CMOS Analog Modules with Parasitic and Mismatch Constraints

The performances of analog circuits depend greatly on the layout parasitics and mismatches.Novel techniques are proposed for modeling the distributed parasitic capacitance,parasitic parameter mismatch due to process gradient and the inner stack routing mismatch.Based on the proposed models,an optimal stack generation technique is developed to control the parasitics and mismatches,optimize the stack shape and ensure the generation of an Eulerian graph for a given CMOS analog module.An OPA circuit example is given to demonstrate that the circuit performances such as unit gain bandwidth and phase margin are enhanced by the proposed layout optimization method.

Design of a 14-Bit 1 MS/s Successive Approximation Analog-to-Digital Converter

A 14-bit successive approximation analog-to-digital converter (SAR ADC) with capacitive calibration has been designed based on the SMIC. 18 μm CMOS process. The overall architecture is in fully differential form to eliminate the effect caused by common mode noise. Meanwhile, the digital-to-analog converter (DAC) is a two-stage structure, which can greatly reduce the area of the capacitor array compared with the traditional DAC structure. The capacitance calibration module is mainly divided into the mismatch voltage acquisition phase and the calibration code backfill phase, which effectively reduces the impact of the DAC mismatch on the accuracy of the SAR ADC. The design of this paper is based on cadence platform simulation verification, simulation results show that when the sampling rate is 1 MS/s, the power supply voltage is 5 V and the reference voltage is 4.096 V, the effective number of bits (ENOB) of the ADC is 13.49 bit, and the signal-to-noise ratio (SNR) is 83.3 dB.

Design and Analysis of Analog Front-End of Passive RFID Transponders

An analog front-end of HF passive RFID transponders compatible with ISO/IEC 18000-3 is presented.Design considerations, especially the power transmission in the RFID transponder, are analyzed. Based on these considerations,an analog front-end is presented with novel architecture, high power conversion efficiency, low voltage, low power consumption, and high performance in an environment of noise and power fluctuation. The circuit is implemented in a Chartered 0.35μm standard CMOS process. The experimental results show that the chip can satisfy the design target well.

A Low-Power 12-Bit SAR ADC for Analog Convolutional Kernel of Mixed-Signal CNN Accelerator

As deep learning techniques such as Convolutional Neural Networks(CNNs)are widely adopted,the complexity of CNNs is rapidly increasing due to the growing demand for CNN accelerator system-on-chip(SoC).Although conventional CNN accelerators can reduce the computational time of learning and inference tasks,they tend to occupy large chip areas due to many multiply-and-accumulate(MAC)operators when implemented in complex digital circuits,incurring excessive power consumption.To overcome these drawbacks,this work implements an analog convolutional filter consisting of an analog multiply-and-accumulate arithmetic circuit along with an analog-to-digital converter(ADC).This paper introduces the architecture of an analog convolutional kernel comprised of low-power ultra-small circuits for neural network accelerator chips.ADC is an essential component of the analog convolutional kernel used to convert the analog convolutional result to digital values to be stored in memory.This work presents the implementation of a highly low-power and area-efficient 12-bit Successive Approximation Register(SAR)ADC.Unlink most other SAR-ADCs with differential structure;the proposed ADC employs a single-ended capacitor array to support the preceding single-ended max-pooling circuit along with minimal power consumption.The SARADCimplementation also introduces a unique circuit that reduces kick-back noise to increase performance.It was implemented in a test chip using a 55 nm CMOS process.It demonstrates that the proposed ADC reduces Kick-back noise by 40%and consequently improves the ADC’s resolution by about 10%while providing a near rail-to-rail dynamic rangewith significantly lower power consumption than conventional ADCs.The ADC test chip shows a chip size of 4600μm^(2)with a power consumption of 6.6μW while providing an signal-to-noise-and-distortion ratio(SNDR)of 68.45 dB,corresponding to an effective number of bits(ENOB)of 11.07 bits.

Design of an Analog Front End for Passive UHF RFID Transponder IC

This paper introduces a high-performance analog front end for a passive UHF RFID transponder IC, which is compatible with the ISO/IEC 18000-6B standard,operating at the 915MHz ISM band with a total supply current consumption less than 8μA. There are no external components, except for the antenna. The passive IC＇s power supply is taken from the energy of the received RF electromagnetic field with the help of a Schottky diode rectifier. The RFID analog front end includes a local oscillator, clock generator, power on reset circuit, matching network and backscatter,rectifier,regulator, and AM demodulator. The IC, whose reading distance is more than 3m,is fabricated with a Chartered 0.35μm two-poly four-metal CMOS process with Schottky diodes and is EEPROM supported. The core size is 300μm × 720μm.

Experimental Research on Multi-lateral Wells by the Electric Field Analogue Model

There is a close theoretical similarity between water pressure gradients in aquifers and applied voltage gradients in aqueous solutions. A series of electric field analogue experiments has been conducted by focusing on symmetrical multi-lateral wells and dual-lateral wells of arbitrary angles between laterals. This research not only evaluates the productivity equations of a symmetrical multi-lateral well showing the effect of angles on productivity, but also proposes the concept of the multi-lateral productivity coefficient. Moreover, the multi-lateral productivity coefficient equation is designed to calculate the productivity of dual-lateral wells of variable angles, which is in turn supported by experiment. It also helps provide the experimental basis for optimizing the configuration, and building the semi-analytic productivity model, of multi-lateral wells.

Laser Measurement and Intensity Evaluation of Intake Swirl in Engine Using a Water Analog

The intake swirl in the cylinder was induced by a swirler which was fixed in one of two intake ports. In order to understand the characteristics of the intake swirl, a transparent water analog was designed which simulated 150 type single cylinder engine. At the same time, the particle image velocimetry was used to measure the flow fields induced by various swirlers in the analog. After measurement, a new method was presented to evaluate the intensity of the intake swirl. Then, when the measured sections, the lifts of valve and the swirlers were different, the calculated results of the flow field were compared.

基于Analog Discovery 2的巨磁阻效应实验系统

将口袋式仪表Analog Discovery 2及其配套控制软件WaveForms引入巨磁阻效应实验,替代直流电源、信号发生器、示波器、数字信号控制器等传统仪表,完成信号的激发、采集以及处理.由Analog Discovery 2驱动螺线管、巨磁阻传感器、直流电机和步进电机等部件,可以实现巨磁阻传感器R-B基本特征曲线和高速转动转速的快速测量,还可以结合齿轮状铁磁体,实现低速转动的准确测量及微小角位移的定标和测量.各主要部件采用三维调整架固定,偏置永磁铁也配备了不同形状的导磁头,方便学生观察不同条件下的实验现象,完成更具有开放性和创新性的实验内容.

Cloning and Analysis of NBS-LRR Type Resistance Gene Analogues in Sweet Potato (Ipomoea batatas)

The degenerate primers were designed based on the conserved NBS-LRR motifs among the known disease-resistance genes. A fragment of about 500 bp was amplified from genomic DNA of sweet potato using the specifically designed degenerate primers. After cloning and sequencing, 20 NBS-LRR type of disease-resistance gene analogue （RGAs） in sweet potato were observed. The deduced amino acid sequence of DNA fragment contains the conserved motifs of NBS-LRR type RGAs, such as P-loop, Kinase-2α, Kinase-3α and GLPL domain. The 20 RGAs could be sorted into two subclasses, namely TIR- NBS-LRR type and non-TIR-NBS-LRR type. Compared with the known resistance genes including N, L6 and M, the percentages of homologous amino acid sequence in 10 TIR-NBS-LRR range between 21% -44%. While other 10 non-TIR-NBS-LRR assume 15% -46% homology with the known resistance genes （Prf, RPM1, RPS2, etc. ）. Consequently the RGAs may further be used as molecular marker for screening the candidate disease-resistance genes in sweet potato.

Treatment of central precocious puberty by GnRH analogs： long-term outcome in men

In boys, central precocious puberty （CPP） is the appearance of secondary sex characteristics driven by pituitary gonadotropin secretion before the age of 9 years. In the last years, relevant improvements in the treatment of CPP have been achieved. Because CPP is rare in boys, the majority of papers on this issue focus on girls and do not address specific features of male patients regarding end results and safety. In the present paper, recent advances of CPP management with GnRH analogs in men are summarized. End results in untreated and treated patients are also reviewed by an analysis of the recently published literature on treatment of CPP in men. The available data indicate that therapy with GnRH analogs can improve final height into the range of target height without significant adverse short-term and long-term effects, but longer follow-up of larger series of patients is still required to draw definitive conclusions.

Multifunctional mixed analog/digital signal processor based on integrated photonics

Photonic signal processing offers a versatile and promising toolkit for contemporary scenarios ranging from digital optical communication to analog microwave operation.Compared to its electronic counterpart,it eliminates inherent bandwidth limitations and meanwhile exhibits the potential to provide unparalleled scalability and flexibility,particularly through integrated photonics.However,by far the on-chip solutions for optical signal processing are often tailored to specific tasks,which lacks versatility across diverse applications.Here,we propose a streamlined chip-level signal processing architecture that integrates different active and passive building blocks in silicon-on-insulator(SOI)platform with a compact and efficient manner.Comprehensive and in-depth analyses for the architecture are conducted at levels of device,system,and application.Accompanied by appropriate configuring schemes,the photonic circuitry supports loading and processing both analog and digital signals simultaneously.Three distinct tasks are facilitated with one single chip across several mainstream fields,spanning optical computing,microwave photonics,and optical communications.Notably,it has demonstrated competitive performance in functions like image processing,spectrum filtering,and electro-optical bandwidth equalization.Boasting high universality and a compact form factor,the proposed architecture is poised to be instrumental for next-generation functional fusion systems.