区域水土流失研究综述

以区域水土流失为主题 ,分析并阐述了该领域的研究现状 ,指出了当前存在的主要问题 ,并对研究的今后发展方向进行了展望。

降水量的BP人工神经网络预测模型及其应用

由于影响因素的复杂性 ,预测降水量具有相当的难度。在假设区域长时间内降水量和蒸发量保持平衡的基础上 ,用 BP人工神经网络建立了陕西省汉中市的降水量预测模型 ,根据前 3个月降水量和蒸发量对降水量资料进行了模拟预测 ,结果认为其准确率为 84% ,合格率为 10 0 %。

旱地作物需水量预报决策辅助系统

旱地作物需水量预报决策辅助系统是利用人工智能技术 ,在 Penman公式的基础上结合现有西北旱区的农学知识、模型以及经验进行系统集成而建立的智能化计算机软件系统 ,该系统是西北地区节水农业专家系统的一个子系统。在生产实践中可为陕西关中地区的冬小麦、夏玉米的栽培作出灌溉方案的决策咨询。

The temporal and spatial evaluation on China's agricultural policy output since 1978

Since reform and opening up, how much contribution has China's implementation of new agricultural policy made to agricultural output? This paper is trying to establish an agricultural policy output econometric model for doing a quantitative analysis of China's new agricultural policy. The results show that China's agricultural policies on agricultural output have an average contribution rate of about 7% since 1978, which is consistent with the OECD's basic forecast. There are obvious temporal and spatial differences. Generally speaking, we can divide the contribution of agricultural policy into three periods, which are the start-up phase from 1978 to 1991 (14 years), the stationary phase from 1992 to 2002 (11 years) and the rising phase from 2003 to 2008 (6 years). In space, the contribution of agricultural policy underwent a process from the all-low in the start-up phase, the gradual increase in the stationary phase to the all-high in the rising phase. Northern and western regions are more sensitive to policies. There are three major factors that can affect the contribution of regional agricultural policies, which are the process of national industrialization strategy, terrain and the level of local finance.

Deformation Monitoring and Forecasting Model Study Based on Grey System Theory

The grey system theory studies the uncertainty of small sample size problems. This paper using grey system theory in the deformation monitoring field, based on analysis of present grey forecast models, developed the spatial multi-point model. By using residual modification, the spatial multi-point residual model eras developed in further study. Then, combined with the sedimentation data of Xiaolangdi Multipurpose Dam, the results are compared and analyzed, the conclusion has been made and the advantages of the residual spatial multi-point model has been proved.

Application of forecasting structural cracks technique of 3D move in Chengdao buried hill

3DMove software, based on the three-dimension structural model of geologic interpretation, can forecast reservoir cracks from the point of view of formation of the structural geology, and analyze the characteristics of the cracks. 3DMove software dominates in forecasting cracks. We forecast the developments and directions of the cracks in Chengbei buried hill with the application of forecasting technique in 3DMove software, and obtain the chart about strain distributing on top in buried hill and the chart about relative density and orientation and the chart about the analysis of crack unsealing. In Chengbei 30 buried hill zone, north-west and north-east and approximately east-west cracks in Cenozoic are very rich and the main directions in every fault block are different. Forecasting results that are also verified by those of drilling approximately accord with the data from well logging, the case of which shows that the technique has the better ability in forecasting cracks, and takes more effects on exploration and exploitation of crack reservoir beds in ancient buried hill reservoirs.

Dynamics of nonlinear error growth and season-dependent predictability of El Nino events in the Zebiak-Cane model

With the intermediate-complexity Zebiak-Cane model, we investigate the 'spring predictability barrier' (SPB) problem for El Nino events by tracing the evolution of conditional nonlinear optimal perturbation (CNOP), where CNOP is superimposed on the El Nino events and acts as the initial error with the biggest negative effect on the El Nino prediction. We show that the evolution of CNOP-type errors has obvious seasonal dependence and yields a significant SPB, with the most severe occurring in predictions made before the boreal spring in the growth phase of El Nino. The CNOP-type errors can be classified into two types: one possessing a sea-surface-temperature anomaly pattern with negative anomalies in the equatorial central-western Pacific, positive anomalies in the equatorial eastern Pacific, and a thermocline depth anomaly pattern with positive anomalies along the Equator, and another with patterns almost opposite to those of the former type. In predictions through the spring in the growth phase of El Nino, the initial error with the worst effect on the prediction tends to be the latter type of CNOP error, whereas in predictions through the spring in the decaying phase, the initial error with the biggest negative effect on the prediction is inclined to be the former type of CNOP error. Although the linear singular vector (LSV)-type errors also have patterns similar to the CNOP-type errors, they cover a more localized area than the CNOP-type errors and cause a much smaller prediction error, yielding a less significant SPB. Random errors in the initial conditions are also superimposed on El Nino events to investigate the SPB. We find that, whenever the predictions start, the random errors neither exhibit an obvious season-dependent evolution nor yield a large prediction error, and thus may not be responsible for the SPB phenomenon for El Nino events. These results suggest that the occurrence of the SPB is closely related to particular initial error patterns. The two kinds of CNOP-type error are most likely to cause a significant SPB. They have opposite signs and, consequently, opposite growth behaviours, a result which may demonstrate two dynamical mechanisms of error growth related to SPB: in one case, the errors grow in a manner similar to El Nino; in the other, the errors develop with a tendency opposite to El Nino. The two types of CNOP error may be most likely to provide the information regarding the 'sensitive area' of El Nino-Southern Oscillation (ENSO) predictions. If these types of initial error exist in realistic ENSO predictions and if a target method or a data assimilation approach can filter them, the ENSO forecast skill may be improved. Copyright (C) 2009 Royal Meteorological Society

A hybrid coupled ocean-atmosphere model and ENSO prediction study

A hybrid coupled ocean-atmosphere model is designed, which consists of a global AGCM and a simple anomaly ocean model in the tropical Pacific. Retroactive experimental predictions initiated in each season from 1979 to 1994 are performed. Analyses indicate that: (1) The overall predictive capability of this model for SSTA over the central-eastern tropical Pacific can reach one year, and the error is not larger than 0.8 degrees C. (2) The prediction skill depends greatly on the season when forecasts start. However, the phenomenon of SPB (spring prediction barrier) is not found in the model. (3) The ensemble forecast method can effectively improve prediction results. A new initialization scheme is discussed.

Algorithm Studies on How to Obtain a Conditional Nonlinear Optimal Perturbation (CNOP)

The conditional nonlinear optimal perturbation (CNOP), which is a nonlinear generalization of the linear singular vector (LSV), is applied in important problems of atmospheric and oceanic sciences, including ENSO predictability, targeted observations, and ensemble forecast. In this study, we investigate the computational cost of obtaining the CNOP by several methods. Differences and similarities, in terms of the computational error and cost in obtaining the CNOP, are compared among the sequential quadratic programming (SQP) algorithm, the limited memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) algorithm, and the spectral projected gradients (SPG2) algorithm. A theoretical grassland ecosystem model and the classical Lorenz model are used as examples. Numerical results demonstrate that the computational error is acceptable with all three algorithms. The computational cost to obtain the CNOP is reduced by using the SQP algorithm. The experimental results also reveal that the L-BFGS algorithm is the most effective algorithm among the three optimization algorithms for obtaining the CNOP. The numerical results suggest a new approach and algorithm for obtaining the CNOP for a large-scale optimization problem.

Application of altimetry data assimilation on mesoscale eddies simulation

Mesoscale eddy plays an important role in the ocean circulation. In order to improve the simulation accuracy of the mesoscale eddies, a three-dimensional variation (3DVAR) data assimilation system called Ocean Variational Analysis System (OVALS) is coupled with a POM model to simulate the mesoscale eddies in the Northwest Pacific Ocean. In this system, the sea surface height anomaly (SSHA) data by satellite altimeters are assimilated and translated into pseudo temperature and salinity (T-S) profile data. Then, these profile data are taken as observation data to be assimilated again and produce the three-dimensional analysis T-S field. According to the characteristics of mesoscale eddy, the most appropriate assimilation parameters are set up and testified in this system. A ten years mesoscale eddies simulation and comparison experiment is made, which includes two schemes: assimilation and non-assimilation. The results of comparison between two schemes and the observation show that the simulation accuracy of the assimilation scheme is much better than that of non-assimilation, which verified that the altimetry data assimilation method can improve the simulation accuracy of the mesoscale dramatically and indicates that it is possible to use this system on the forecast of mesoscale eddies in the future.

基于人工神经网络的PC钢棒力学性能预报模型

提出一种PC钢棒抗拉强度的人工神经网络模型方法,采用4×9×1的三层前向BP网络结构,模型主要因素为淬火温度、回火温度、含碳量和单位长度质量。经1500余次训练后,误差平方和

全信息精细储层预测方法研究与实践-以周清庄油田沙三段油藏为例

With the continuously proceeding of petroleum exploratory development in China, exploratory development becomes more and more difficult. For increasing reserve volume and production, lithologic hydrocarbon reservoir has been the most workable, potential and universality exploration targets. In the past, Dagang Oil Field use the complicated fault reservoir theory as the guide, develop and form a suit of matching construction and instrument in prospecting complicated fault reservoir that reach top of exploration industry in China. But the research of lithologic hydrocarbon reservoir is not much, which affects the exploitation progress of lithologic hydrocarbon reservoir. In this thesis, is object, through the depth study of lithologic deposition in Shasan segment of Zhouqingzhuang Oil Field, a suit of holographic fine reservoir bed forecasting techniques is built up and finally gets following main results: 1. Applying geology, seism, drilling, logging and other information to sensitivity preferences, geological model, inversion and integrated stratum evaluation, realizing the method and flow of refined multi-information stratum forecast. 2. Built up a full three dimensional fine structural interpretation method: in view of r problem of accurately demarcating 90% inclined well, propose a inclined well air space demarcating method, make bed demarcating more exactly; in view of problem of faults demarcating and combination in seismic interpretation, propose a computational method of seismic interference based on wavelet translation, make identify the fault in different level more dependable and reasonable; for exactly identifying structural attitude, propose a velocity modeling method under multi-well restriction, make structural attitude closer to the facts. 3. Built up a high accuracy reservoir bed inversion method: in view of problem in exactly identifying reservoir and nonreservoir with conventional wave impedance inversion method in this place, propose a reservoir log response characteristic analysis and sensible log parameter inversion method. ①analysis log response of reservoir and nonreservoir in region of interest, make definite the most sensible log parameter in identifying reservoir and nonreservoir in this region; ②make sensible log parameter inversion based on wave impedance inversion, to improve inversion accuracy, the thickness of recognizable reservoir bed reach 4-5m. 4. Built up a 4-D reservoir forcasting circuit: in view of difficulty that in lithologic hydrocarbon reservoir making reservoir space characteristic clear by using structural map and reservoir forecasting techniques once only, propose a 4-D reservoir forcasting circuit. In other words, based on development conceptual design, forcast reservoir of different time, namely multiple 3D reservoir forcasting in time queue, each time the accuracy degree of reservoir forcasting is improved since apply the new well material, thereby achieve high quality and highly efficient in exploratory development. During exploratory development lithologic depositin in Shasan segment of Zhouqingzhuang Oil Field, there are thirteen wells get 100% success rate, which sufficiently proves that this suit of method is scientific and effective.

砂泥岩储层测井产能预测方法研究

Productivity prediction is very important in the exploration and development of oilfields. Using well log data to predict productivity is a front-line technology， which is key issue in petroleum exploration phase. The essential factors of productivity prediction is building practical models and correcting various causes to improve precision of prediction parameters. Any errors of parameters selections can affect the calculation of productivity prediction; therefore， how to improve research means and calculation accuracy is an important task of productivity prediction. Theory and case examples are deeply and comprehensively studied in the paper. Based on the theory of mud-filtrate invasion and experimental results， the damage of drilling， cementing， perforating，acidizing and fracturing were investigated. The damage depth was quantitatively evaluated by log data， based on this， the processing results of reservoir sensitivity were used to analysis quantitatively the damage of reservoir. The productivity prediction and reservoir damage were initiatively incorporated according to well logging， and the precision of productivity prediction was effectively improved. The method of NMR was explored to calculate the fluid viscosity on the basis of reservoir physical method， and the differences between the two methods were compared in the paper. From the theory fluid flow in porous media， various of theoretical models of production prediction were explored and several practical models were consided， such as productivity index method， improved productivity index method， improved Bearder method， SVM and so on. The characteristic and the application scope of these methods were studied. The inflow productivity and outflow productivity were incorporated and nodal analysis method was used to forecast wellhead yield， thus achieved scientifically production. On the applied background of conventional logging suite， the applying of special items or new logging method which is practical in the research area were studied， the logging suite was further optimized， and the precision of forecast was improved. On the basis of the modeling and the calculation of parameters， these methods were verified and analyzed， and the reconstruct principle was also built for block reservoir. The research block was processed by these methods and compared with testing data. Based on above the research， a technological system which is practical for shaly sand profiles in Shengli Oilfield was built. The system can reach commercialized degree，and satisfied the need of exploration and development of the oilfield.

辽东湾隐蔽油气藏地球物理识别技术研究

In China and world, more than half the recent basin discovered reserves involve lithologic hydrocarbon reservoir reserves. The major target for further hydrocarbon basin exploration is the subtle reservoir. The Liaodong Bay prospect is much important in Bohai Sea, which includes Liaoxi low uplift, Liaodong uplift, Liaoxi sag and Liaozhong sag. After dozens years’ exploration in Liaodong Bay, few unexplored big-and-middle-sized favorable structural traps are remained and most of the stock structure targets are bad for fragmentary. Thus seeking for new prospect area and making a breakthrough, have become the unique way to relieve the severe exploration condition in Liaodong Bay. Technique Route Based on the petrophysical property of target area, the seismic forward inference of typical subtle trap model is expanded with analysis of logging, seismic and geologic data. According to petrophysical characteristics and forward inference and research on seismic response of actual seismic data in target area, the optimization of geophysical technique is used in subtle trap identification and the geophysical identification technique system of subtle reservoir is formed. The Key Research ① Petrophysical Model The petrophysical parameter is the basic parameter for seismic wave simulation. The seismic response difference of rocks bearing different fluids is required. With the crossplot of log data, the influence of petrophysical parameters on rock elastic properties of target area is analyzed, such as porosity, shale index, fluid property and saturation. Based on the current research on Biot-Gassmann and Kuster-Toksoz model, the petrophysical parameter calculator program which can be used for fluid substitution is established. ② S-wave evaluation based on conventional log data The shear velocity is needed during forward inference of AVO or other elastic wave field. But most of the recent conventional log data is lack of shear wave. Thus according to the research on petrophysical model, the rock S-wave parameter can be evaluated from conventional log data with probability inverse method. ③ AVO forward modeling based on well data For 6 wells in JZ31-6 block and 9 wells in LD22-1 block, the AVO forward modeling recording is made by log curve. The classification of AVO characteristics in objective interval is made by the lithologic information. ④ The 2D parameter model building and forward modeling of subtle hydrocarbon trap in target area. According to the formation interpretation of ESS03D seismic area, the 2D parameter model building and seismic wave field forward modeling are carried on the given and predicted subtle hydrocarbon trap with log curve. ⑤ The lithology and fluid identification of subtle trap in target area After study the seismic response characteristics of lithology and fluid in given target area, the optimization of geophysical technique is used for lithology identification and fluid forecast. ⑥The geophysical identification technique system of subtle reservoir The Innovative Points of this Paper ① Based on laboratory measurement and petrophysical model theory, the rock S-wave parameter can be evaluated from conventional log data with probability inverse method. Then the fluid substitution method based on B-G and K-T theory is provided. ② The method and workflow for simulating seismic wave field property of subtle hydrocarbon trap are established based on the petrophysical model building and forward modeling of wave equation. ③ The description of subtle trap structural feature is launched. According to the different reflection of frequency wave field structural attribute, the fluid property of subtle trap can be identified by wave field attenuation attribute and absorption analysis. ④ It’s the first time to identify subtle trap by geophysical technique and provide exploration drilling well location. ⑤ The technique system of subtle reservoir geophysical identification is formed to provide available workflow and research ideas for other region of interest.

天然气藏地震识别技术研究

The Research of Seismic Recognition Techniques for Gas Reservoir Shang Yong_sheng(Geophysics) Directed by Yang Chang-chun Abstract Gas reservior is one of the most important nature resources. Someone forecast that the output will exceed crude oil in 2015 and become the largest energy source. Recently,more and more gas reservior are discovered as the oil field and gas filed exploration go deep into development. Although the gas proved reserves rise greatly the explorative degree of natural gas resource in our country is still very low. The potential of gas exploration is very great and our task is so hard. How to recognise and discover new gas reservoir is the first task based on the great gas reservior resources foreground. the gas reservior in different oil and gas field have its special gas generation, reservoiring, physical property conditions. However,it may have the same geophysical characters. So,it is very important to analyse, research, summarizing the geophysical characters of the gas reservior and make use of the characters to identify the gas layer effectively. This paper start with modeling,and it discuss the geophysical characters of the gas reservior response. It analyse the seismical wave characters of the gas reservoir. Furthermore, it summarize the method of using the seismica profile to identify the gas reservior directly. The paper discuss the research of extracting diffraction wave for mass diffraction wave grow at the edge of the gas reservoir at the seismic section. Making use of the technique of extracting diffraction wave to identify the gas reservior is the first experiment of the gas reservoir prediction technique. The avo technology is a new geophysical method. From the pre-stack analysis, this paper discuss the technique of using the rich information to identify the gas reservoir. Based on the case study of the Qidam basin and the Hailaer basin it discuss the method of predicating gas reservoir using pre-stack information. It include pre-stack amplitude preserve process, AVO modeling, fluid replacement technique, AVO analysis and interpretation technique. The paper summarize a gas reservoir prediction procedure focusing on the pre-stack information. The seismic wave will cause great attenuation when it pass through the gas layer and the high frequency component loss. This paper discuss the technique of extracting seismic attributes to represent the attenuation degree of seismica wave. Based on the attenuation attributes,it does the research of the gas reservor identification and prediction. At last,the paper discuss the method of calculating the azimuthal anisotropy to predict the fracture reservoir. Keyword: gas reservoir, diffraction wave, AVO, attenuation attribute,fracture prediction