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作者简介:

陈元千(1933—),男,河南兰考人,教授级高级工程师,1952年考入清华大学石油工程系,1956年毕业于北京石油学院钻采系,长期从事油气藏工程、油气田开发和油气储量评价工作。联系电话:(010)83595952,E-mail:525980269@qq.com。

通讯作者:

傅礼兵(1985—),男,江西新余人,高级工程师,博士。联系电话:(010)83595161,E-mail:fulibing@petrochina.com.cn。

中图分类号:TE33

文献标识码:A

文章编号:1009-9603(2019)06-0087-05

DOI:10.13673/j.cnki.cn37-1359/te.2019.06.011

参考文献 1
Arps,J.J.:Analysis of decline curve,Trans.AIME(1945)160,228-247.
参考文献 2
Arps,J.J.:Estimation of primary oil reserves,Trans.AIME(1956)207,182-186.
参考文献 3
陈元千,周翠:线性递减类型的建立、对比与应用,石油学报,2015,36(8)983-987. Chen Yuanqian,Zhou Cui:Establishment,comparison and appli⁃ cation of the linear decline type,Acta Petrolei Sinica,2015,36(8)983-987.
参考文献 4
陈元千,唐玮:油气田剩余可采储量、剩余可采储采比和剩余可采程度的年度评价方法,石油学报,2016,37(6)796-801.Chen Yuanqian,Tang Wei:Annual evaluation methods for re⁃ maining recoverable reserves,remaining recoverable reservesproduction ratio and remaining recoverable degree of oil and gas fields,Acta Petrolei Sinica,2016,37(6)796-801.
参考文献 5
陈元千,唐玮:广义递减模型的建立及应用,石油学报,2016,37(11)1 410-1 413.Chen Yuanqian,Tang Wei:Establishment and application of gen⁃ eralized decline model,Acta Petrolei Sinaca,2016,37(11)1 410-1 413.
参考文献 6
陈元千,吕恒宇,傅礼兵,等:注水开发油田加密调整效果的评价方法,油气地质与采收率,2017,24(6)60-64.Chen Yuanqian,Lü Hengyu,Fu Libing,et al:Evaluation method of infilling adjustment effect for waterflooding development oil⁃ fields,Petroleum Geology and Recovery Efficiency,2017,24(6)60-64.
参考文献 7
陈元千,胡丹丹,赵庆飞,等:注聚合物提高采收率幅度的评价方法及应用,油气地质与采收率,2009,16(5)48-51.Chen Yuanqian,Hu dandan,Zhao Qingfei,et al:Evaluation meth⁃ od and its application of enhancing recovery efficiency range of polymer-flooding,Petroleum Geology and Recovery Efficiency,2009,16(5)48-51.
参考文献 8
陈元千,周翠,张霞林,等:重质油藏注蒸汽开采预测经济可采储量和经济极限汽油比的方法——兼评国家行业标准的预测方法,油气地质与采收率,2015,22(5)1-6.Chen Yuanqian,Zhou Cui,Zhang Xialin,et al:Methods for pre⁃ dicting economically recoverable reserves and economic limit of steam-oil ratio of heavy oil reservoir by steam flooding recovery:comment on the prediction methods of the national industry stan⁃ dard,Petroleum Geology and Recovery Efficiency,2015,22(5)1-6.
参考文献 9
陈元千,周游,李秀峦,等:利用SAGD开采技术预测重质油藏可采储量新方法,特种油气藏,2015,22(6)85-89.Chen Yuanqian,Zhou You,Li Xiulan,et al:A new method of us⁃ ing SAGD exploitation technique to predict the recoverable re⁃ serves of heavy oil reservoir,Special Oil & Gas Reservoirs,2015,22(6)85-89.
参考文献 10
陈元千,齐亚东,傅礼兵,等:井控页岩气可动地质储量和可采储量的评价方法,油气地质与采收率,2018,25(4)73-78.Chen Yuanqian,Qi Yadong,Fu Libing,et al:Methods for estimat⁃ ing well-controlled movable in-place and recoverable reserves of shale gas,Petroleum Geology and Recovery Efficiency,2018,25(4)73-78.
参考文献 11
Barton,C.C.,Lapont,P.R.:Fractals in petroleum geology and earth processes,Springer,New York,(1995)59-72.
参考文献 12
陈元千,李剑,李云波,等:利用典型曲线拟合的递减常数预测油气藏的可采储量,中国海上油气,2015,27(5)49-54. Chen Yuanqian,Li Jian,Li Yunbo,et al:Using decline constants from matching type curve to predict recoverable reserves of oil and gas reservoirs,China Offshore Oil and Gas,2015,27(5)49-54.
参考文献 13
何培,冯连勇,Tom Wilber:马塞勒斯页岩气藏单井产量递减规律及可采储量预测,新疆石油地质,2015,36(2)249-252.He Pei,Feng Lianyong,Tom Wilber:Production decline rule and recoverable reserves prediction of Marcellus shale gas well in a production unit,Pennsylvania,US,Xinjiang Petroleum Geology,2015,36(2)249-252.
目录contents

    摘要

    Arps基于矿场油井产量递减数据的统计分析和理论研究,提出了指数、双曲线和调和三种经典的递减模型,受到世人的高度重视,至今被广泛地应用于全球油气工业的产量和可采储量的评价。应当指出,Arps的指数递减是递减率为常数且产量递减较快的一种递减模型。由于其预测的指标比较稳妥,被上市评估公司普遍采用。Arps 的双曲线递减和调和递减是两种产量递减较慢的模型,在实际中应用得并不多。陈元千等于2015年建立的线性递减模型,仅适用于产量随时间呈直线下降,而且递减率随时间的增加而增加。本文建立的幂函数递减模型,它的递减率随时间的增加而降低。根据Arps提出的递减指数n划分的不同递减模型:n =-1时为线性递减,n =0时为指数递减,0<n <1时为双曲线递减,n =1时为调和递减,1<n ≤2时为幂函数递减。由于呈幂函数递减的产量与时间之间存在双对数直线关系,因此,该递减又可称为双对数递减。利用幂函数递减模型,对两口美国页岩水平气井的产气量、累积产气量、经济可采储量、采出程度和递减率进行预测。预测结果表明,两口井的递减指数基本相同,接近于2。

    Abstract

    Based on statistical analysis and theoretical research on the declining production data of oilfield oil wells,Arps proposed three classical decline models of exponential,hyperbolic and harmonic,which have been highly valued by the world and have been widely used in the evaluation of global oil and gas industry production and recoverable reserves. It should be noted that the Arps exponential decline is a decline model in which the decline rate is constant and the produc- tion is declining faster. Because the predicted indicators are relatively stable,it is widely adopted by evaluation companies. The hyperbolic and harmonic declines of Arps are two models with slower decrement,which are not widely used in practice. The linear decline model established by Chen Yuanqian et al.in 2015 is only applicable to the linear decline of production over time,and the decline rate increases with time. The power function decline model is established in this paper,and its decline rate decreases with time. According to the decline exponent n proposed by Arps:linear decline model n =-1,expo- nential decline model n =0,hyperbolic decline model 0<n <1,harmonic decline model n =1,power function decline model1< n ≤2. Due to the double logarithmic linear relationship between the production and time of the divergence of the power func- tion,the decline model can be referred to as a double logarithmic decline model. By using the power function decline mod- el,the production,cumulative production,economically recoverable reserves,recovery and decline rate of two shale horizon- tal gas wells in America are predicted. The prediction results show that the decline exponents of the two wells are almost the same and close to 2.

  • 产量递减法是预测油气井、油气藏和油气田产量和可采储量的重要方法。它的应用不受油气藏的储集类型、驱动类型、流体类型和开采方式的限制,只要进入了产量递减阶段,即可进行方法的选择和有效的应用。Arps[1-2] 于1945年和1956年提出了指数、双曲线和调和三种经典递减模型。其中指数递减模型应用最为广泛,而双曲线递减模型应用较少,调和递减模型出现的概率很低。这主要与三种递减模型的适用性和预测结果的可靠性有关。陈元千等于2015年提出的线性递减模型[3],仅适用于压裂后投产而产量递减较快的致密性砂岩和页岩的油气井和油气藏。陈元千等于2016年建立的广义递减模型[4-5],对注水开发油田的加密调整效果[6]、注聚合物溶液的三次采油效果[7] 和重质原油热力开采的效果[8-9] 可以作出有效评价。对于致密、超致密的砂岩油气藏和页岩油气井,若在经水力压裂投产后,产量较低,递减较快,可采用线性或指数递减模型进行评价[10]。而对于投产后产量递减较慢的页岩水平气井,可利用笔者建立的幂函数递减模型,进行产气量、累积产气量和经济可采储量、采出程度和递减率的预测。

  • 1 幂函数递减模型的建立

  • Pareto于1897年提出的负指数幂函数表达式[11] 为:

  • y=ax-b
    (1)
  • 由(1)式可以看出,当 x=0时,y 趋于无穷大,这是该函数的一个特点,也是它的一个缺陷。为了将 (1)式用于产量递减,对(1)式作如下修正:

  • y=a(1+x)-b
    (2)
  • 这样,由(2)式可以看出,当x=0时,y=a,而不是无穷大。若将y改为产量qx改为时间t,由(2)式得幂函数递减的产量为:

  • q=a(1+t)-b
    (3)
  • 由(3)式可以看出,当 t=0时,q=a,而 a 就是 t=0时的初始理论产量 qi。为了确定(3)式中常数ab 值,将该式取自然对数得:

  • lnq=α-βln(1+t)
    (4)
  • 其中:

  • α=lna, 或 a=eα
    (5)
  • β=b
    (6)
  • 由(4)式可以看出,q与(1+t)之间呈双对数直线关系,故幂函数递减又可称为双对数递减。

  • 已知累积产量与产量的关系为:

  • Gp=0t qdt
    (7)
  • 将(3)式代入(7)式,经积分后得幂函数递减的累积产量为:

  • Gp=a1-b(1+t)1-b-1
    (8)
  • 若经过经济评价确定了经济极限产量qEL后,那么,由(3)式可得与其相对应的经济极限生产时间为:

  • tEL=aqEL1b-1
    (9)
  • 将(9)式代入(8)式,得幂函数递减的经济可采储量为:

  • GR=a1-baqEL1-bb-1
    (10)
  • 由(8)式除以(10)式,得可采储量的采出程度为:

  • R=(1+t)1-b-1aqEL(1-b)b-1
    (11)
  • 由(3)式对时间求导得:

  • dqd(1+t)=-ab(1+t)-b-1
    (12)
  • 已知Arps定义的递减率[1] 为:

  • D=-dqqd(1+t)
    (13)
  • 将(3)式和(13)式代入(12)式,得幂函数的递减率与时间的关系式为:

  • D=b1+t
    (14)
  • 由(14)式可以看出,幂函数递减的递减率随时间的增加呈双曲线降低,当 t=0时,D=Di =b,故由(14)式得:

  • D=Di1+t
    (15)
  • 2 不同递减模型的对比

  • 表1列出了按Arps递减指数划分的不同递减模型:n=-1时为线性递减;n=0时为指数递减;0<n<1时为双曲线递减;n=1时为调和递减;1<n ≤2而 n=1/Di 时为幂函数递减。表1中的无因次产量 qD=q/qi,无因次递减率DD=D/Di,无因次时间tD=Dit

  • 表1 不同递减模型的nDDDqqD的对比

  • Table1 Comparisons of nDDDq and qD for different decline models

  • 绘制不同递减模型的无因次产量与无因次时间的典型曲线。由图1可看出,线性递减(n=-1)的典型曲线处在最左边,其次是指数递减(n=0)的典型曲线,接着是双曲线递减(n=0.5)和调和递减(n=1)的典型曲线,最右边的是幂函数递减(n=2)的典型曲线。利用实际生产的产量递减数据与典型曲线拟合[12],可以判断递减模型,确定递减常数和评价可采储量。

  • 图1 不同递减模型无因次产量qD与无因次时间tD的关系

  • Fig.1 Plot of qD and tD of different decline models

  • 绘制不同递减模型的无因次递减率 DD与无因次时间 tD的关系曲线。由图2可以看出,不同递减模型的递减率随时间变化的理论关系,幂函数递减是递减最慢的一种递减模型。

  • 图2 不同递减模型的无因次递减率DD与无因次时间tD的关系

  • Fig.2 Plot of DD and tD of different decline model

  • 3 应用实例

  • 美国宾夕法尼亚州阿巴拉琴盆地的Marcellus页岩气藏[13],A井和B井两口页岩水平气井投产后的生产数据绘于图3。按照(4)式的关系,将两口井的生产数据绘于双对数坐标系统中,由图4看出,在双对数坐标系统中,两口井的q与1+t具有很好的直线关系,经(4)式的线性回归求得A井的α=6.760 8, β=0.522 6,相关系数 r=0.983 3;B井的 α=6.138 1,β=0.52 6 6,相关系数 r=0.985 7。由(5)式和(6)式分别求得:A井的 a=863.33和 b=0.526 6;B井的 a=462.88和b=0.522 6。

  • 图3 A井和B井产量曲线

  • Fig.3 Production curves of Well A and Well B

  • 图4 A井和B井的lnq与ln(1+t)的关系

  • Fig.4 Plot of lnq vs.ln(1+t)of Well A and Well B

  • 将两口井的 ab 值分别代入(3)式,得预测A井和B井的产量关系式分别为:

  • q=863.33(1+t)-0.5266
    (16)
  • q=462.88(1+t)-0.5226
    (17)
  • 再将A井和B井的 ab 值分别代入(6)式,得预测两口井的累积产量关系式分别为:

  • Gp=1823.68(1+t)0.4734-1
    (18)
  • Gp=969.58(1+t)0.4774-1
    (19)
  • 最后,将两口井的abqEL值分别代入(11)式,得预测A井和B井的采出程度关系式分别为:

  • R=5.13×10-2(1+t)0.4734
    (20)
  • R=8.95×10-2(1+t)0.4774
    (21)
  • 将两口井的 b 值分别代入(11)式,得预测A井和B井的递减率的关系式分别为:

  • D=0.52661+t
    (22)
  • D=0.52261+t
    (23)
  • 将(16)式和(17)式预测两口井的产量数据绘于图3。由图3看出,预测结果与实际生产数据符合得较好。由(18)式和(19)式预测两口井的累积产气量绘于图5。由图5可以看出,预测结果与实际生产数据也符合得很好。由(20)式和(21)式预测两口井的采出程度绘于图6。由(22)式和(23)式预测两口井的递减率绘于图7。由图7看出,尽管两口井的产气量与可采储量相差明显,但递减率曲线几乎重合。

  • 图5 A井和B井的Gpt的关系图

  • Fig.5 Plot of Gp vs.t of Well A and Well B

  • 图6 A井和B井的Rt的关系图

  • Fig.6 Plot of R vs.t of Well A and Well B

  • 图7 A井和B井的Dt的关系图

  • Fig.7 Plot of D vs.t of Well A and Well B

  • 若设页岩水平气井生产的月经济极限产量qEL=30×104 m3/mon,将该值与两口井的ab值分别代入 (10)式,可得A井和B井的经济可采储量分别为:

  • GR=863.331-0.5266863.33301-0.52660.5266-1=3.5543×108m3
    (24)
  • GR=462.881-0.5226462.88301-0.52260.5226-1=1.0837×108m3
    (25)
  • 4 结论

  • 通过对Pareto于1897年提出的负指数幂函数的修正和推导,建立了幂函数递减模型。该递减模型是对由Arps提出的指数递减、双曲线递减、调和递减模型以及由陈元千提出的线性递减模型所构成的递减模型序列的重要补充和完善。Arps提出的递减指数 n 是判断和划分递减模型的重要参数。递减指数愈大,产量的递减愈慢。线性递减的 n=-1,双曲线递减的0<n<1,调和递减的 n=1,幂函数递减的1<n ≤2。因此,幂函数递减是最慢的一种递减模型,而且产量开始递减得快,而后逐渐变慢。

  • 实际工作经验表明,利用Arps的指数递减和双曲线递减模型,以及陈元千的线性递减模型,对于页岩水平气井的产量和可采储量的预测,有时达不到比较可靠的结果。然而,利用笔者建立的幂函数递减模型,对两口页岩水平气井的产量、累积产量、经济可采储量和递减率的预测,取得了比较满意的结果。两口井的递减指数几乎相同,接近于2,属于递减最慢的类型。预测两口井的经济可采储量并不高,分别为3.554 3×108 m3 和1.083 7×108 m3,这可能与两口水平井的水平段较短有关。

  • 符号解释

  • y —幂函数的因变量;

  • x —幂函数的自变量;

  • q —气井的产量,104 m3/d或104 m3/mon;

  • qi—气井的初始理论产量(qi=a),104 m3/d或104 m3/mon;

  • qD —气井的无因次产量,dim;

  • qEL —气井的经济极限产量,104 m3/d或104 m3/mon;

  • Gp —气井的累积产量,104 m3

  • GR —气井的经济可采储量,104 m3

  • t —生产时间,d或mon;

  • tD —无因次生产时间,dim;

  • tEL —经济极限的生产时间,d或mon;

  • n —递减指数,dim;

  • D —递减率,d-1 或mon-1

  • Di —初始理论递减率,d-1 或mon-1

  • DD —无因次递减率,dim;

  • R —可采储量的采出程度,frac;

  • ab —幂函数递减方程的常数;

  • αβ —幂函数递减双对数直线的截距和斜率。

  • 参考文献

    • [1] Arps,J.J.:Analysis of decline curve,Trans.AIME(1945)160,228-247.

    • [2] Arps,J.J.:Estimation of primary oil reserves,Trans.AIME(1956)207,182-186.

    • [3] 陈元千,周翠:线性递减类型的建立、对比与应用,石油学报,2015,36(8)983-987. Chen Yuanqian,Zhou Cui:Establishment,comparison and appli⁃ cation of the linear decline type,Acta Petrolei Sinica,2015,36(8)983-987.

    • [4] 陈元千,唐玮:油气田剩余可采储量、剩余可采储采比和剩余可采程度的年度评价方法,石油学报,2016,37(6)796-801.Chen Yuanqian,Tang Wei:Annual evaluation methods for re⁃ maining recoverable reserves,remaining recoverable reservesproduction ratio and remaining recoverable degree of oil and gas fields,Acta Petrolei Sinica,2016,37(6)796-801.

    • [5] 陈元千,唐玮:广义递减模型的建立及应用,石油学报,2016,37(11)1 410-1 413.Chen Yuanqian,Tang Wei:Establishment and application of gen⁃ eralized decline model,Acta Petrolei Sinaca,2016,37(11)1 410-1 413.

    • [6] 陈元千,吕恒宇,傅礼兵,等:注水开发油田加密调整效果的评价方法,油气地质与采收率,2017,24(6)60-64.Chen Yuanqian,Lü Hengyu,Fu Libing,et al:Evaluation method of infilling adjustment effect for waterflooding development oil⁃ fields,Petroleum Geology and Recovery Efficiency,2017,24(6)60-64.

    • [7] 陈元千,胡丹丹,赵庆飞,等:注聚合物提高采收率幅度的评价方法及应用,油气地质与采收率,2009,16(5)48-51.Chen Yuanqian,Hu dandan,Zhao Qingfei,et al:Evaluation meth⁃ od and its application of enhancing recovery efficiency range of polymer-flooding,Petroleum Geology and Recovery Efficiency,2009,16(5)48-51.

    • [8] 陈元千,周翠,张霞林,等:重质油藏注蒸汽开采预测经济可采储量和经济极限汽油比的方法——兼评国家行业标准的预测方法,油气地质与采收率,2015,22(5)1-6.Chen Yuanqian,Zhou Cui,Zhang Xialin,et al:Methods for pre⁃ dicting economically recoverable reserves and economic limit of steam-oil ratio of heavy oil reservoir by steam flooding recovery:comment on the prediction methods of the national industry stan⁃ dard,Petroleum Geology and Recovery Efficiency,2015,22(5)1-6.

    • [9] 陈元千,周游,李秀峦,等:利用SAGD开采技术预测重质油藏可采储量新方法,特种油气藏,2015,22(6)85-89.Chen Yuanqian,Zhou You,Li Xiulan,et al:A new method of us⁃ ing SAGD exploitation technique to predict the recoverable re⁃ serves of heavy oil reservoir,Special Oil & Gas Reservoirs,2015,22(6)85-89.

    • [10] 陈元千,齐亚东,傅礼兵,等:井控页岩气可动地质储量和可采储量的评价方法,油气地质与采收率,2018,25(4)73-78.Chen Yuanqian,Qi Yadong,Fu Libing,et al:Methods for estimat⁃ ing well-controlled movable in-place and recoverable reserves of shale gas,Petroleum Geology and Recovery Efficiency,2018,25(4)73-78.

    • [11] Barton,C.C.,Lapont,P.R.:Fractals in petroleum geology and earth processes,Springer,New York,(1995)59-72.

    • [12] 陈元千,李剑,李云波,等:利用典型曲线拟合的递减常数预测油气藏的可采储量,中国海上油气,2015,27(5)49-54. Chen Yuanqian,Li Jian,Li Yunbo,et al:Using decline constants from matching type curve to predict recoverable reserves of oil and gas reservoirs,China Offshore Oil and Gas,2015,27(5)49-54.

    • [13] 何培,冯连勇,Tom Wilber:马塞勒斯页岩气藏单井产量递减规律及可采储量预测,新疆石油地质,2015,36(2)249-252.He Pei,Feng Lianyong,Tom Wilber:Production decline rule and recoverable reserves prediction of Marcellus shale gas well in a production unit,Pennsylvania,US,Xinjiang Petroleum Geology,2015,36(2)249-252.

  • 参考文献

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    • [3] 陈元千,周翠:线性递减类型的建立、对比与应用,石油学报,2015,36(8)983-987. Chen Yuanqian,Zhou Cui:Establishment,comparison and appli⁃ cation of the linear decline type,Acta Petrolei Sinica,2015,36(8)983-987.

    • [4] 陈元千,唐玮:油气田剩余可采储量、剩余可采储采比和剩余可采程度的年度评价方法,石油学报,2016,37(6)796-801.Chen Yuanqian,Tang Wei:Annual evaluation methods for re⁃ maining recoverable reserves,remaining recoverable reservesproduction ratio and remaining recoverable degree of oil and gas fields,Acta Petrolei Sinica,2016,37(6)796-801.

    • [5] 陈元千,唐玮:广义递减模型的建立及应用,石油学报,2016,37(11)1 410-1 413.Chen Yuanqian,Tang Wei:Establishment and application of gen⁃ eralized decline model,Acta Petrolei Sinaca,2016,37(11)1 410-1 413.

    • [6] 陈元千,吕恒宇,傅礼兵,等:注水开发油田加密调整效果的评价方法,油气地质与采收率,2017,24(6)60-64.Chen Yuanqian,Lü Hengyu,Fu Libing,et al:Evaluation method of infilling adjustment effect for waterflooding development oil⁃ fields,Petroleum Geology and Recovery Efficiency,2017,24(6)60-64.

    • [7] 陈元千,胡丹丹,赵庆飞,等:注聚合物提高采收率幅度的评价方法及应用,油气地质与采收率,2009,16(5)48-51.Chen Yuanqian,Hu dandan,Zhao Qingfei,et al:Evaluation meth⁃ od and its application of enhancing recovery efficiency range of polymer-flooding,Petroleum Geology and Recovery Efficiency,2009,16(5)48-51.

    • [8] 陈元千,周翠,张霞林,等:重质油藏注蒸汽开采预测经济可采储量和经济极限汽油比的方法——兼评国家行业标准的预测方法,油气地质与采收率,2015,22(5)1-6.Chen Yuanqian,Zhou Cui,Zhang Xialin,et al:Methods for pre⁃ dicting economically recoverable reserves and economic limit of steam-oil ratio of heavy oil reservoir by steam flooding recovery:comment on the prediction methods of the national industry stan⁃ dard,Petroleum Geology and Recovery Efficiency,2015,22(5)1-6.

    • [9] 陈元千,周游,李秀峦,等:利用SAGD开采技术预测重质油藏可采储量新方法,特种油气藏,2015,22(6)85-89.Chen Yuanqian,Zhou You,Li Xiulan,et al:A new method of us⁃ ing SAGD exploitation technique to predict the recoverable re⁃ serves of heavy oil reservoir,Special Oil & Gas Reservoirs,2015,22(6)85-89.

    • [10] 陈元千,齐亚东,傅礼兵,等:井控页岩气可动地质储量和可采储量的评价方法,油气地质与采收率,2018,25(4)73-78.Chen Yuanqian,Qi Yadong,Fu Libing,et al:Methods for estimat⁃ ing well-controlled movable in-place and recoverable reserves of shale gas,Petroleum Geology and Recovery Efficiency,2018,25(4)73-78.

    • [11] Barton,C.C.,Lapont,P.R.:Fractals in petroleum geology and earth processes,Springer,New York,(1995)59-72.

    • [12] 陈元千,李剑,李云波,等:利用典型曲线拟合的递减常数预测油气藏的可采储量,中国海上油气,2015,27(5)49-54. Chen Yuanqian,Li Jian,Li Yunbo,et al:Using decline constants from matching type curve to predict recoverable reserves of oil and gas reservoirs,China Offshore Oil and Gas,2015,27(5)49-54.

    • [13] 何培,冯连勇,Tom Wilber:马塞勒斯页岩气藏单井产量递减规律及可采储量预测,新疆石油地质,2015,36(2)249-252.He Pei,Feng Lianyong,Tom Wilber:Production decline rule and recoverable reserves prediction of Marcellus shale gas well in a production unit,Pennsylvania,US,Xinjiang Petroleum Geology,2015,36(2)249-252.