小断层
范各庄矿南六采区小断层发育规律研究

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小断层对煤与瓦斯突出的影响分析

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三维构造解释中的小断层识别技术及应用

众所周知,断层解释是构造解释中很重要的一部分,因为断裂与油气的运移、聚集成藏等过程是息息相关的。
它既可以是油气运移的通道,也可以是油气聚集成藏的遮挡。
所以在含油气盆地内,掌握断裂系统的分布是至关重要的。
在常规的构造解释中,解释人员通常是根据地震剖面上同相轴的错断、扭曲、分叉、合并等形态特征或者是特殊波的出现来识别断层的。
但是受地震分辨率的限制,对于小断层,采用常规方法来进行断层解释是很困难的,本文综合运用三维相干体技术、沿层倾角方位角技术,针对小断层的识别进行研究。
(1)相干原理。
三维相干数据体技术是利用三维地震数据体中相邻道地震信号之间的相似性,来描述地层和岩性的横向非均匀性的。
当底层存在断层或者是岩性发生突变的时候,相邻道地震信号之间的相干性会变差,由此便可以识别细小的断层,或者研究岩性的横向非均匀变化,以识别特殊地质体的边界。
设有两个离散信号序列、,则其互相关函数:(1)其中,是和的互相关函数:(2)其中,k是时窗宽度。
方程(2)可以改写为:(3)由相关原理可知:再令:(4)则:由上述式子可以看出,当地下介质为横向均匀并且连续的时候,则与完全相干,可知接近于零;当地下存在有断层或者是岩性突变时,则会导致与的相干性变差,接近于2。
据此,应用(4)式对三维地震数据体进行数学变换,可以得到三维的相干数据体,在三维相干数据体的时间切片中可以清晰的识别出地下的细小断层。
(2)沿层倾角方位角扫描原理。
沿层倾角方位角技术是沿层倾角及方位角的综合,而沿层倾角方位角的计算也是主要依据已追踪的层位数据。
假设由A1 ̄A9按顺序组成的方阵,代表着层位数据中相邻的九个点的T值,则可以定义沿层倾角及方位角如下:其中,为倾角,为方位角,g是A4和A6的差与A4、A6之间距离的比值,即,h是A8和A2的差与其两点间距离的比值,即。
由倾角和方位角的定义可以看出,输入层位数据的质量对倾角及方位角的影响比较大,要想取得较为理想的效果,要求输入的层位数据是完全自动追踪和内插的,一定不能做平滑处理。
掘进工作面遇小断层的判断和处理方法

掘进工作面遇小断层的判断和处理方法
小断层是指断层带中不太强烈的破裂带,可以引起掘进工作面的
不稳定。
掘进面在遇到小断层时,需要进行判断和处理。
以下是处理
方法:
1. 判断小断层:掘进工作面在进入矿层之前,需要通过地质调
查和钻探等手段,对可能的小断层进行评估和预测。
在掘进工作面中,需要根据岩石的裂隙、变形和破碎程度等特征,判断是否遇到了小断层。
2. 处理小断层:在判断遇到小断层后,需要采取相应的处理措施,以保证掘进工作面的安全和稳定。
常用的处理方法包括:(1)加强支护:在小断层附近加强支护,可以通过增加钢架数
量和密度、加厚钢架固定片、改进锚杆安装方式等手段,提高支护的
抗震、抗压能力。
(2)加强前后地质预测:通过加强前后地质预测,可提高对小
断层等地质难点的了解,进一步优化掘进工作面的支护方案和掘进进度。
(3)采取隧道补充法:在小断层处采用隧道补充法,即将断层
段削去,再对隧道进行拱顶和侧壁支护的一种方法,可以保证掘进工
作面的稳定和安全。
综上所述,掘进工作面在遇到小断层时,需要根据具体情况,采
取相应的处理措施,以保证工作面的安全、高效和稳定。
利用地面钻孔测井资料推测解释小断层

利用地面钻孔测井资料推测解释小断层在煤矿开采、掘进过程中,小断层、小构造往往是冒顶、突水、瓦斯突出等灾难事故的主要诱发因素。
因此小构造、小断层的精确探测解释对于煤矿的开采具有重大的意义。
在煤矿实际开采过程中,由于构造应力的作用,在小断层周围经常发现局部的构造煤。
构造煤的存在,导致剖面上显示局部异常,此种特征可作为判断小断层的依据。
地球物理测井资料富含很多地质信息,如岩煤层定性及确定煤层的深度和厚度;鉴定沉积环境;煤质分析和岩性分析;确定地层的强度特性;进行地层对比及勘查区的评价;确定煤的级别;地质年代界面的划分;断层点的解释等。
可以通过对比进行合理运用破解测井曲线密码。
1测井定性解释小断层1.1测井曲线定性分析特征在潘三井田范围内,利用已有的钻孔测井资料,结合构造分区及其层间距对比,划分出受构造影响不同程度区域内的钻孔,针对这些钻孔的测井资料进行定性分析,识别出不同岩性的测井曲线形态特征,及其受构造影响的岩性的测井曲线形态特征。
在小断层发育的地带,最显著的“证据”之一就是构造煤、构造岩,根据国内外研究及其相关资料表明,视电阻率测井曲线和伽马伽马测井曲线对其响应比较显著,同时参考自然电位测井曲线,因此本文主要采用视电阻率和伽马伽马测井曲线来定性解释小断层。
1.2构造煤的测井响应特征煤层受到构造应力破坏后,致使构造软煤分层的裂隙增多,孔隙度和水分含量增大,离子导电性增强,导致构造软煤的电阻率降低,视电阻率测井曲线表现为明显的低幅值,并且会出现分叉现象或者锯齿状形态,因此视电阻率曲线是构造软煤定性和定厚的主要曲线。
由于构造煤煤体结构破坏,煤的密度减小,散射的伽马射线增多,其强度就增大,因此,构造软煤比硬煤具有较大的人工伽马值。
1.3受构造影响的砂质泥岩的测井响应特征由于受构造影响,砂质泥岩的岩体结构造成破坏,裂隙增加,主要表现为视电阻率的减小,视电阻率测井曲线形态呈现低幅值,接近于纯泥岩的幅值,并且呈现出微齿状。
从哈克教授的幼小断层理论看法国的幼小衔接措施

从哈克教授的幼小断层理论看法国的幼小衔接措施哈克教授的幼小断层理论是指幼儿园与小学之间存在着不同的教育理念和教学方法,在幼小衔接时存在着一定的断层。
在这种情况下,幼儿园和小学的衔接措施变得尤为重要。
本文将通过分析哈克教授的幼小断层理论,探讨法国的幼小衔接措施,并提出相应的建议。
首先,哈克教授的幼小断层理论认为,幼儿园与小学存在着不同的教育理念和教学方法。
幼儿园注重培养孩子的综合素养和认知能力,强调以游戏为主导的教育活动。
而小学则注重学科内容的教学和学习,强调课堂教学的系统性和规范性。
这种教育理念和方法的不同导致了幼小衔接的断层问题。
因此,为了解决这个问题,法国采取了一系列的幼小衔接措施。
首先,法国通过制定统一的学习目标,确保幼儿园和小学在教学内容上的衔接。
幼儿园和小学的教育部门共同制定了学习目标和课程标准,确保幼儿园的教育内容能够为小学的学习打下坚实的基础。
其次,法国通过加强教师培训和沟通,促进幼儿园和小学之间的教学衔接。
法国政府鼓励幼儿园教师和小学教师进行沟通和交流,互相了解对方的教学方式和要求,以确保幼儿园和小学之间的教学衔接更加顺畅。
此外,法国还鼓励幼小合并教育机构,创造更好的教学环境和条件。
幼小合并的教育机构能够更好地整合幼儿园与小学的教育资源和课程设置,使幼儿园和小学之间的衔接更加自然和无缝。
除了这些措施之外,我认为法国还可以进一步加强幼小衔接的研究和实践。
应该通过调研和实践,深入了解幼小衔接中存在的问题和困难,针对性地采取措施,促进幼小衔接的顺利进行。
此外,法国还可以加大对幼小衔接的宣传和推广力度,提高家长和社会对幼小衔接的认识和重视程度。
总之,幼小衔接对于一个国家的教育体系来说至关重要,而哈克教授的幼小断层理论提供了一个有价值的视角来研究和解决幼小衔接中的问题。
通过分析法国的幼小衔接措施,我们可以看到他们在解决幼小衔接断层问题上所做的努力。
然而,还有一些可以改进的地方,我提出了一些建议,希望能对今后的研究和实践有所启发。
李嘴孜矿小断层分布规律

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矿井掘进工作面小断层识别及处理

矿井掘进工作面小断层识别及处理摘要:由于现代矿山高强度开采,巷道掘进量也随之大量增加。
煤巷、半煤岩巷岩巷年掘进量超过15000km。
随着安全高效机械化采矿技术在的应用,掘进速度和支护质量的要求也越来越高。
近年矿山科技的迅速发展,科研院校、企业等就巷道快速掘进技术进行了研发,将新工艺、新技术、新装备应用于安全高效的现代化煤矿中。
关键词:矿井掘进;工作面;小断层识别;处理1引言近几年来,我国煤矿巷道掘进事业发展迅猛,不仅掘进施工技术水平还是掘进的机械装备等都有了迅猛的发展,掘进机械化水平有了较大的提高。
但是,我国煤矿掘进技术水平与世界先进国家相比,仍有较大差距,特别是岩巷掘进技术差距大。
以国有重点煤矿为例,每年岩巷掘进进尺煤矿巷道是煤矿井下生产的脉络。
据不完全统计,我国煤矿事业发展迅速,每年的掘进量都在突飞猛进的不断增长,据不完全统计不全已经超过了10000km,实现煤矿巷道的快速掘进,保持其畅通和完好,对矿井正常生产和安全生产具有重要意义。
在煤矿生产矿井的井巷开拓工程中,岩巷快速掘进占有很重要的地位,岩巷是构成生产矿井采区或生产水平接替的主要链锁工程项目;在生产矿井井巷开拓工程量中,岩巷占有很大比重,约上巷道开拓总量的20%。
近几年,随着开采方法口技术的发展,岩巷在巷道开拓总工程量的比重不断下降,但对于老矿区来说岩巷在巷道开拓总量中仍占15-20%。
同时不少矿井随着生产能力的。
不断扩大,矿井开拓延伸速度更快,导致采掘关系更为紧张。
因此,不断提高岩巷掘进速度,对保证煤矿采掘关系正常发展尽快形成采区或生产水平的生产系统,进一步缓解掘进工艺紧张状况,对促进矿井稳步施工生产十分有帮助。
2矿井快速掘进技术2.1综掘机快速掘进技术①综掘机配单体气动锚杆钻机支护技术特点:该技术是我国目前应用最为广泛,技术比较成熟,适应一般地质条件的巷道掘进与支护其存在的问题主要是掘进与支护交替顺序作业,掘进效率低,劳动强度大。
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Research on Development Character of Middle and Small Size Fault Structure in DongPang Mine Field on Fractal TheorySun Xue-yangSchool of Geology and Environment Xi’an University of Science and TechnologyXi’an, Chinasunxy02211@Xia Yu-chengSchool of Geology and Environment Xi’an University of Science and TechnologyXi’an Chinaxiayc@Abstract—Middle and small size fault structure is the key geological factor affecting the safety production of DongPang mine field.Finding out development character of middle and small fault structure in DongPang mine field is to provide the geological premise for mining design of coal mine and working face layout. Based on the analysis of real data, 20 factors affecting the development of middle and small fault structure are summarized. And on the fractal theory, the fault fractal dimension value is worked out ;and then the key factors affecting the development of middle and small fault structure are filtrated by means of regression analysis, finally the relation of fault fractal dimension and the key factors affecting fault structure development is analyzed by using the grey relational analysis method. The results showed that fault fractal dimension can be used as comprehensive index of quantity, scale, combination form, horizontal extending length and inhomogeneity of distribution of fault structure. And the bigger its value is, the more fault structure is developed. Hence, fault fractal dimension is a reliable index denoting development degree of middle and small fault structure in DongPang mine field.Keywords: fault fractal dimension; middle and small size fault structure; fractal theory; DongPang mine field of ChinaI.I NTRODUCTIONA lot of researches have indicated that the distribution of fault structure and geometric shape have the fractal structures[1-2]. Fractal feature of fault structure with different scales of crust has been studied respectively by Turcotte, Li Ben-liang, Lu Xin-wei, Shen Zhong-min etc, it was pointed out that the spatial distribution characteristics and self-similarity of fault structure can be described quantitatively by fractal value, Berry and Lewis hold that the size of fractal value of fault system is a comprehensive embodiment of quantity, scale, combination form of fault and dynamic mechanism.[3-6] Fault structure in DongPang mine field developed very well, according to statistics there are nearly 200 faults. Middle and small fault structure is the key geological factor affecting coal production. According to the data of the districts where the middle and small fault structure had been disclosed, influencing factors of fault development are analyzed and summarized; in unmined districts, the degree of medium feature. And so analyzing the feature of middle and small fault structure development is very important and basic work. Based on Fractal Theory in the paper, research shows that fault reference cone is reliable index denoting development degree of middle and small fault structure.II.T HE FACTORS BEINGfault development will be forecast by structuralLIKELY TO AFFECT THESng mineitions of the factors affecting thed tureeasures(Mxhd):the totalormality of the thickness of coal meaMxhd_pjz ķIn the equationof coness of main mineof the thickness of coal seamMchd_pjz ĸIn the equatof cooverlying strata (JyhDEVELOPMENT OF MIDDLE AND SMALL FAULTTRUCTURE AND QUANTIZATION OF ITS INDEXESProceed from the actual conditions of DongPafield, the factors which are likely to affect middle and small fault structure development are fined for 14 indexes, and the features of fault development are fined to 6 indexes.A.The definevelopment of middle and small fault strucand the method of quantization(1)The thickness of coal mof thickness of shanxi formation and taiyuan formation(2)Abnsures(Mxhdyc): The difference between borehole thickness of coal measures and average thickness of coal measures in DongPang mine fieldMxhdyc˙Mxhdˉķ , Mxhd_pjz is average thickness al measures in DongPang mine field(3)coal seam thickness(Mchd): thickable coal seam(4)Abnormality(Mchdyc): the difference between borehole or unit thickness of coal seamand average thickness of coal seam in DongPang mine fieldMchdyc˙Mchdˉionĸ, Mchd_pjz is average thickness al seam in DongPang mine field(5)Bedrock thickness of coald):Total thickness of strata above main mineable coal seam, namely not including thickness of overlying strata series of main mineable coal seam of loose overburden layer2010 International Conference on Computing, Control and Industrial Engineering(6)Thickness of loose layer of coal overlying strata (Ssc): The total of thickness of tertiary and quaternary(7)Elevation of coal floor(Dbbg): Altitude of main mineable coal floor, namely structure fluctuation status of main mineable coal seam present(8)Abnormality of elevation of coal floor(Dgbf): change range of elevation of main mineable coal floor presentBased on trend analysis of elevation of coal floor, trend value d is obtained ; subtract the trend value d from measured value z, the residual value is r. Let the average value of all the positive residual values (namely r>0) dd as the standard of measuring the elevating of measured coal floor of one borehole abnormal or not, namely abnormal limit. If the residualvalue of one borehole r>0, is denoted by R +. If R +-dd>0,then that the elevation of coal seam floor is abnormal; if R +-dd<0,then that the elevation of coal seam floor is within the abnormal limit , namely normal. Conversely, the residual value of one borehole r<0, is denoted R -. If R --dd>0,then that the elevation of coal seam floor is within the abnormal limit; if R --dd <0,then that the elevation of coal seam floor is abnormal. For one unit, if abnormality of elevation of coal floor of the unit is calculated, abnormality values of the unit’s searching field need to be weighted and averaged.(9)The maximal apparent dip of coal seam (Mcqj): In the element, the maximal apparent dip of coal seam is defined as the maximal value of apparent dip of coal seam(¢)of all borehole sites .The apparent dip of coal seam of borehole sites is defined as the difference (h) between the elevations of borehole coal floor and that of central coal floor (obtained from weighted average of the elevations of all borehole coal floor in the element) and the arc tangent function of the quotient of level distance (d)from the borehole to the midpoint of the unit, namely:¢=arctan (h/d) Ĺ(10)The basement elevation of coal measures (Mxjd)˖The altitude of bottom surface of benxi formation or (when benxi formation is absent) taiyuan formation(11)The difference between the elevation of main mineable coal floor and the basement elevation of coal measures.Mc_jy ˙Dbbg-Mc_jy ĺ(12)Integrated hardness of overburden strata of coal seam(Psyd)˖hardness of the upper overburden strata series of main mineable coal seam, namely anti destructive capabilityIn the research of the geotechnical engineering and mining subsidence, the common classification method of rock is Protodyakonov taxonomy which was put forward by M.M. Protodyakonov at 1926.The determination method of classification index is as follow:q = Rpress/1000 ĻIn the equation Ļ: q-Protodyakonov coefficient, also called rock rigidity coefficient; Rpress-uniaxial compressive strength of rock(N/cm 2).Fig.1.Calculationmethod of Tbyy and Bbyy Based on rock hardness coefficient, the overburden synthesis Protodyakonov rigidity is defined as follow:¦¦nini i mq m Q 11/ļIn the equation ļ: Q ˉthe overburden synthesis Protodyakonov rigidity; m i ˉstratified thickness of normal of overburden strata unit: m; q i ˉstratified evaluation coefficient of lithology of overburden strata i, also called rock rigidity coefficient; n- the stratified number of overburden strata(13)Influence coefficient of hard rock within 30m above coal seam roof(Tbyy): anti destructive capability of coal seam roof¦ ni i i L h Tbyy 1)]1/([ ĽIn the equation Ľ: n üthe layer number of hard rock within 30m above coal seam floor; i üthe layer numbers of hard rock; h i ü the layer thickness of hard rock ; Li üthe distance between bottom surface of hard rock and top surface of coal seam,which is showed in Fig.1.(14)Influence coefficient of hard rock within 20m above coal seam floor (Bbyy): anti destructive capability of coal seam floor. The calculation method is similar to that of influence coefficient of hard rock, within 30m above coal seam roof, which is showed in Fig.1.B.definition of divided data of development features of fault structure and its method of quantizationBy comparison of the results of qualitative analysis on fault structure of mine and results of fractalstudy, it is obtained that fault fractal dimension is a comprehensive embodiment of fault amount , scale ,combination form, horizontal extending length and inhomogeneity of distribution, and can be a quantitative index of complex degree of fault structure . By the research result of fractal dimension on fault fracture in DongPang mine field , it can be also proved that fault fractal dimension is a comprehensive index of fracture quantity, group number, and length of fracture trace, fracture cutting relation and inhomogeneity of fracture distribution, and evaluating complex degree of fault structure block section by fault network has the advantage that other indexes can not compare.In order to study and compare the complex degrees of each unit fracture, fault fractal dimension of unit Ds is measured by grid-covered method. The calculation method is : let each side of the element into two, can be divided into 4 square lattices whose side length is 1/2 of side length of unit(denoted by R ),the number of lattices of faults entering N(R/2) is calculated out, then , each of square lattices with the side length , 1/2 of side length of unit are divided respectively into square lattices whose side length is 1/4 of side length of unit, and the number of lattices of faults entering N(R/4) is calculated out respectively,… analogy in turn, namely side length of square lattices is changed by the rate of 1/2, and the number of relevant lattices is calculated N(r) .If there is a self-similar structure in faults of research are, there is the following relation:lnN(r)=A+Bln(r) ľBased on least square method or one-dimensional linear regression analysis, can be obtained the slope of straight line and correlation coefficient of linear equation and standard deviation of it, absolute value of linear slope, namely fault fractal dimension of research area, namely : Ds = |B|In order to compare, were calculated out the indexes of evaluation unit(Dcts), including its fault density(Dcmd), number of faults(Dcts), fault length(Dccd), fault throw(Dcdj), fault intensity(Dcqd ) etc. Among them, fault intensity is defined as:¦ u ni i i L h Dcqd 1][ ĿIn the equation Ŀ, n üfault quantity of unit; i üfault number; hi üfault throw; Li ülength of evaluation unit.III.A NALYSIS ON THE MAIN AFFECTING FACTORSOF MIDDLE AND SMALL SIZE FAULT STRUCTUREMining area one, two, three, six, seven and nine have been exploited in DongPang mine field at present. Moreover, part of middle and small faults are disclosedin some roadways .The area is regarded as proved area which is divided into 73 grids with 4004h 400,20 evaluation index values of every unit are calculated ,can be obtained the original data of quantitative analysis. Due to the limited space, they are not been listed here. And then, based on the quantitative analysis methods of gradual regression analysis method, grey relational analysis method and corresponding analysis method etc, main controlling factors of affecting the development of middle and small faults in DongPang mine field are screened out to lay a foundation for development degree prediction of fault fracture in non-mining areas.A.analysis method of gradual regressionAccording to the need of analysis method of gradual regression, the factors need to be predicted are for dependent variable, and that prediction factors for independent variable. A threshold is given(F*), then according to the threshold, independent variable is screened automatically by computers ,the main perdition factors are reserved, independent variable ,secondary or independent are rejected, finally a best regression equation is presented.Here fault fractal dimension is regarded as dependent variable, other 19 indexes are regarded as independent variable which have analyzed by gradual regression.According to the need of calculation program, dependent variable must be at the last column, so the movement of fault fractal dimension Dcfw(X14) is changed into (X20)(X14)--fault throw Dcdj (X15) —cap thickness of bedrock(X16)—coal seam-base thickness Mc_jy (X17)—hard rock effect of roof Tbyy; (X18)—hard rock effect of floor (X19)—thickness of unconsolidated layers DŽWhen F*=0.1, regression equation is: Y=0.2368411+0.00099X(2)-0.052X(9)+0.002X(11)+0.047X(12)+0.0088X(13)-0.005X( 14)+0.014X(17)-0.03X(18)-0.00059X( 19)Multiple correlation coefficient = .818163172251713Standard deviation = 3.00181281861453E-02 F checkup value =14.17305When multiple correlation coefficient is 81.8%, shows that in the equation, the relation of independent variable combination and the relation of dependent variable are close. Significance test is done, F0.05(20,60)=1.75;F0.01(20,60)=2.20;r0.05(80)=0.352;r0.01(80)=0.413 are obtained by lookup. This shows that whether F test or test of correlation coefficient, when confidence level is 0.01, regression equation is obvious, that is to say, the equation is credible.By the analysis on the equation, the influencing factors of fault fractal dimension are: (X2)—abnormality of thickness of coal measures (X9)—comprehensive hardness of overlying strata (X11)—fault length(X12)—fault number Dcts (X13)—fault density Dcqd (X14)üfault throw Dcdj;(X17)—hard rock effect of roof (X18)—hard rock effect of floor Bbyy(X19)—thickness of unconsolidated layers SscWhen in the range of 0.2-3,class indexes of fault are always preserved in the regression equation; When F* is taken respectively as 2.5 and 3, only class indexes of fault are left(X11)-(X13).This showed that fault fractal dimension and class indexes of fault are in a close relation.Besides class indexes of fault, the other independent variables which are chosen are all for medium indexes of structure, namely, comprehensive hardness of overlying strata , effect coefficient of hard rock of roof, effect coefficient of hard rock of floor, abnormality of thickness of coal measures and thickness of unconsolidated layers.B. grey correlation analysis methodCorrelation analysis of grey system is mainly used to analyze dynamic relationship between various factors of system and its features which changes with time, and then the main factors of system can be obtained. In the process of development of system, if the change situation of the two factors is basically consistent, namely, synchronous change degree is higher, and then it is considered that the relationship of the two factors is close or correlation degree is larger; or correlation degree of the two factors is smaller. So, correlation degree is quantitative description of correlation degree between various factors of system. Because fault fractal dimension is comprehensive embodiment of fault number, scale, combination form, level extension length and heterogeneous distribution, and can be a quantitative index ,therefore ,it is used as mother factor, and the other 19 factors likely related to fault fractal dimension are used as son factors.Correlation degrees between fault fractal dimension (X14) and its influencing factors are obtained by computing as follows: G(14,1)=.875; G(14,2)=.305; G(14,3)=.873; G(14,4)=.555;G(14,5)=.861; G(14,6)=.83; G(14,7)=.866;G(14,8)=.865; G(14,9)=.872; G(14,10)=.925; G(14,11)=.918; G(14,12)=.925; G(14,13)=.864; G(14,14)=1.;G(14,15)=.857;G(14,16)=.859;G(14,17)=.868;(14,18)=.838; G(14,19)=.858; G(14,20)=.874DŽThe sorting of influencing factors of fault fractal dimension is as follows:Fault density(X10), fault number(X12), fault length(X11), thickness of coal measures(X1), thickness of unconsolidated layers(X20), coal seam thickness(X3), comprehensive hardness of overlying strata(X9), coal seam-base thickness(X17), maximum apparent dip of coal seam(X7), basement elevation of coal measures(X8), fault density(X13), floor elevation of coal seam(X5), cap thickness of bedrock(X16), hard rock effect of floor(X19), fault throw(X15), hard rock effect of roof(X18), amplitude of floor elevation(X6), abnormality of coal seam thickness(X4) andabnormality of coal measures(X2).Fig.2 Forecast sub-area chat of relative complexity degree of faults in DongPang coal field. I:boundary of coal field; II:bound of goaf; III: isoclines offault fractal dimension; IV:faults IV.P ARTITION ESTIMATE AND FORECAST OF RELATIVE COMPLEXITY DEGREE OF FAULT STRUCTURES DongPang mine field is divided into 331 unitsaccording to a grid spacing of 350m h 350m, including74 units in disclosed areas. All the fault fractaldimension values in the mine field are predicted by the above network. According to relative complexity degree of fault structures, the division standards are thefollowing: grade I ---fault fractal dimension value İ0.3; grade II ---0.3˘fault fractal dimension value ˘0.7; grade III --- fault fractal dimension value ı0.7.The mine f ld is divided into 3 kinds of districts (Fig.2): relatively simple district of structure---transverse shading, filling with pale green; relatively complex district of structure---cross shading, filling with peachblow; and the middle structure between the two districts ---oblique shading, filling with pale red.Based on Fig.2, comparative development units i ie n disc in Fi According to the whole prediction values of fau fract (1)Thickness c ts abnormality,com is a close relation between fault fractal dime values of fault class are pred R EFERENCES[1]Benoit B. Mandelb l geometry of nature f chaos, scale invariance and i,Sun Yan,ect. Significance of ctal dimension of fault jia ,ect.fractal e weierstrass mandelbrot fractal losed areas, a majority of them are part of relatively complex districts or middle structure districts; the units whose faults are thin relatively are part of relatively simple districts. The result of prediction is coincident with the actual situation : the monoclinic area in south is greater part of relatively simple districts of structure; almost all fault-folded area in north is relatively complex districts of structure.However, the obvious contradiction can be found g. 2: in the east segment of middle fault zone, south of mining area 9, and mining area 6 and 8 is found many of faults, but the result of prediction is relatively simple districts of structure.lt al dimension of unit ,the contour map was plotted (Fig. 3).It showed that fault fractal dimension of a part of units is less than 0, and just in the district (in Fig. 3,the district with the cross shading ,filling withpink ),often there are more fault development .If the units with its fault fractal dimension ˘0 are also fallen under relatively complex districts of structure, the contradiction above can be solved in some extent.V.C ONCLUSIONSof oal measures, i prehensive hardness of overlying strata, hard rock effect of floor, hard rock effect of roof, thickness of unconsolidated layers ,thickness of coal seam , coal seam-base thickness ,are in the front rank of relational order and in the optimum regression equation respectively ; it shows that the relative complexity degree of fault structure is in association with coal measures and sedimentary characteristics of overlying strata, especially with hardness , there is more closer association.(2)There nsion and class indexes of fault. This showed that fault length, fault density ,fault number and fault intensity comprehensively and can be indeed used as comprehensive index of fault number, fault scale, combination form,horizontal extending length and inhomogeneity of distribution.(3)When evaluation index icted in undisclosed areas, only consider fault fractal dimension,fault length ,fault number ,fault density , fault intensity and other indexes are not necessary to be predicted one by one .And so fault fractal dimension is a reliable index of development degree of middle and -small faults in DongPang Mine Field.rot. The fracta (updated and augmented edition)[M].New York:W. H. Freeman and Company ,1983.[2]Turcotte D L. Implication o fractal statistics in geology[J].Global and Planetary Change ,1990,3(3):301-308.[3]Li Ben-liang,Zhang Xi-hu dimension value of fault systems in evaluating natural resources with tibet as an example[J]. Geological journal of china universities ,1999,5(1):17—21.[4Lu xin-wei and ma dong-sheng. fra systems and antimony deposit distribution in central hunan[j]. Geological review, 1998, 44(5)˖ 542—546.[5]Shen zhongmin; feng zujun zhou guang dimension of fault system and oil field distribution[J]. Earth science, 1995,20(1):75—78.[6]Berry m v, lewis z v. on th function[J]. proceedings of the royal society of london(series a). mathematical and physical sciences ,1980,370:459—484.Fig.3 Isoclines of forecasting the fault fractal dimensionI:boundary of coal field; II:bound of goaf; III: isoclines of fault fractal dimension; IV:faults。