Journal of Chemical and Pharmaceutical Research, 2014, 6(12): Research Article

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1 Avalable onlne Journal of Chemcal and Pharmaceutcal Research, 2014, 6(12): Research Artcle ISSN : CODEN(USA) : JCPRC5 Analyss on nfluencng factors of well productvty n tght ol reservor wth gray correlatve method L Zhongxng 1, Jang Shan 2*, Zhao Jyong 1, Qu Xuefeng 1 and Le Qmng 1 1 Exploraton & Development Research Insttute of Petro Chna Changqng Olfeld Company, X an, Shaanx, Chna 2 MOE Key Laboratory of Exploraton Technology for Ol and Gas Resources (Yangtze Unversty), Wuhan, Hube Chna ABSTRACT The objectve of ths study s to fnd out the key factors of well productvty n tght ol reservor. Accordng to the analyss of nfluence factors, eght factors are selected by takng the Chang 7 reservor n Ordos basn for example. Gray correlatve method s used to calculate the eght parameters correlaton and check the nfluences on well productvty. The result shows that: sand volume, ntal ol saturaton, resstvty, nterval transt tme, porosty, perforaton thckness, permeablty and thckness effects on well producton are smaller and smaller. The enrchment zones of Chang 7 reservor are selected by usng the results. Average well producton n enrchment zones s 11.88m 3 /d, whch s sgnfcantly hgher than 6.43m 3 /d of the other regons. Gray correlatve method s effectve and convenent to analyze well productvty parameters n tght ol reservors. Keywords: Tght ol, gray correlatve method, well productvty, nfluencng factors INTRODUCTION Tght ol s the ol that gathers n the tght reservor wthout long dstance mgraton[1,2]. Whle the staged fracturng technology of horzontal well becomes more and more mature, exploraton and development of tght ol reservors have acheved great breakthrough n USA. In Chna, tght ol s the most realstc reservor at unconventonal ol-gas resources and wll be an mportant breakthrough n ol exploraton[3].well productvty s the key factor that restrctng the development of tght reservor. There s an mportant sgnfcance to ascertan man factors of productvty for the development of tght ol reservors. Many factors affect the well productvty and there s a complex relatonshp between them. What s more, each factor has dfferent degree of nfluence on the sngle well productvty. Gray correlatve analyss method quanttatvely characterzes the degree of assocaton between factors accordng to the acquantance of the trend factors and reveals the varous mpact on performance ndex[4,5]. Ths paper determnes the correlaton between parameters and well productvty by selectng parameters affectng well productvty accordng to the theory of grey correlatve analyss method. Then, some factors that nfluence well productvty were sorted by usng gray correlatve analyss method, there are 11 wells that are used as research subjects at Chang 7 reservor of Ordos Basn regon. The results provde way to select enrchment zones of well n the tght reservors. INFLUENCE FACTORS OF PRODUCTIVITY Fracturng s needed to obtan ndustral productvty n tght reservor, whch s of poor physcal property, strong heterogenety and complcated pore structure[6,7]. There are many factors to nfluence the well productvty n tght sandstone reservors. They can be dvded nto three categores: Geologcal factors, flud propertes and engneerng parameters[8,9]. Geologc factors nclude reservor thckness, permeablty, ntal ol saturaton and so on. Flud propertes contan vscosty, densty, etc. Engneerng factor manly refers to perforaton length, fracturng parameters and well completon method. Flud propertes are always the same n the same reservor. The paper 635

2 screens a number of factors from the geologcal factors and engneerng factors by usng statstcal methods, whch control well productvty at Chang 7 reservor of Ordos Basn regon. Geologcal Factors The geologcal factors manly nclude porosty, permeablty and thckness of the reservor. The reservor pore space s the set of crude ol. Porosty and ol productvty are generally a postve correlaton. The large the permeablty, the hgher the producton may be. The reservor thckness s thck wth abundant reserve and the producton s lkely to be hgher. Hydrocarbon-bearng Property Hydrocarbon-bearng property manly refers to the ol saturaton. Ol flowng though the tny capllary does not satsfy Darcy s law. Tght sandstone reservor s hydrophlc. Ol saturaton s hgher, elastc expanson and wckng effect s stronger, so well producton s hgher. Engneerng Factors Engneerng parameters contan perforaton length, fracturng parameters etc. Perforaton length relatng to the extent of reservor n contact wth the wellbore affects the rate of ol flow nto the wellbore. Fracturng manner and fracturng scale have a great nfluence on the morphology and length of fracture. The amount of pre-flud and proppant are parameters to evaluate the fracturng scale n ths paper. GREY CORRELATIVE ANALYSIS PRINCIPLES The basc dea of grey correlatve analyss s based on the sequence smlarty of the curve geometry to determne whether t s closely related. The closer the curves of correspondng sequence are, the greater the correlaton s[4]. The purpose of gray correlatve analyss s the quanttatve characterzaton of correlaton between factors. The theory of grey correlatve method are descrbed below. (1) Determnng the reference numbers. Evaluaton system s decded accordng to the evaluaton purpose. On the base of the collectng evaluaton data, the parent sequence and chld sequences s determned. The parent sequence denotes as: X = ( x (1), x (2), x (3), L, x ( m)) Whre,X 0 parent sequence; x elements; m the number of samples. (2) Data dmensonless. Due to dfferent dmensons and magntude, t generally requres to turn the orgnal data nto dmensonless one. There are many dmensonless methods, such as mean transformaton, ntal transformaton, standardzaton transformaton and so on. Growth sequence uses the ntal transformaton. Mean transformaton s used to turn the general comparatve sequence nto dmensonless one. (3) Calculated the absolute dfference between chld sequences and parent sequence. It s expressed below: = 0 k=1,,n;=1,,m x k x k (4) Takng the maxmum and mnmum values from the absolute dfference. n m mn mn 0 = 1 k = 1 mm = x k x k and n m m ax m ax 0 = 1 k = 1 M M = x k x k (5) Calculatng the correlatve coeffcents ξ (k) between chld sequences and parent sequence. ξ ( k) = mm + ρ MM x ( k) + ρ MM 636

3 Where, ρ s resoluton factor, the value s between 0 and 1, whch reflects the dstngushng ablty. The hgher the value s, the stronger the dstngushng ablty s. In general, ρ=0.5. (6) Calculatng correlatve coeffcents. n 1 γ ( X 0, X ) = ξ ( k) n k = 1 (7) Rankng correlatve coeffcents. Correlatve coeffcents are sorted to obtan comprehensve evaluaton factors. GREY CORRELATIVE ANALYSIS IN THE INFLUENCE FACTORS OF PRODUCTIVITY Chang 7 layer n Ordos Basn s typcal of tght sandstone reservor, whch s closely lnked to shale layer. Its permeablty s generally um 2 [10-12]. Dameter of pore-throat s nano-scale, generally 10~1000nm, wth average scale of about 100um[10,12]. Due to dense formaton and complex mgraton law, well productvty s affected by many factors n tght reservor. In ths paper, eght parameters are used for gray correlatve analyss. These eght parameters nclude physcal propertes, ol saturaton and engneerng factors n Chang 7 formaton. The orgnal data s shown n table 1. Table 1 Orgnal Data of 11 wells Well Qo φ Rs Name /(m 3 /d) /% /Ω m AC/(um/s) H K So L M /m /md /% /m /m 3 An An An An An An An An An An An Where, Q o ol producton, φ porosty, Rs resstvty, AC nterval transt tme, H formaton thckness, K permeablty, S o ntal ol saturaton, L perforaton length, M sand volume. Determne parent sequence and chld sequences Snce the purpose of ths study was to determne the effects of varous factors on productvty, ol producton of 11 well s chosen. Remanng factors are chld sequences: porosty, resstvty, nterval transt tme, formaton thckness, permeablty, ntal ol saturaton, perforaton length, sand volume (Table 2). Table 2 Sample Data Factor φ Rs AC H K So L M Qo /% /Ω m /(um/s) /m /md /% /m /m 3 /(m 3 /d) Symbol X 1 X 2 X 3 X 4 X 5 X 6 X 7 X 8 X 0 Table 3 Correlatve coeffcent, correlaton and correlatve rankng results Factor Φ Rs /% /Ω m AC /(um/s) H K So L M /m /md /% /m /m correlatve coeffcent correlaton correlatve rankng

4 Calculatng Correlatve Coeffcent Accordng to the dmensonless method, turn the orgnal data to dmensonless one. Correlatve analyss s done between chld sequences and parent sequence. The results are shown n Table 3. Accordng to the results of gray correlaton analyss, the prmary and secondary factors that nfluence well productvty are shown n the Fg.1: sand volume, ntal ol saturaton, resstvty, nterval transt tme, porosty, perforaton length, permeablty and formaton thckness. Correcton Φ Rs AC H K So L M Factors Fg.1 Results of gray correlatve analyss. Example Applcatons Well productvty s a key factor n the development of tght reservor, t s of great sgnfcance to choose the enrchment zone. Because resstvty and nterval transt tme respectvely reflect the characterstc of ntal ol saturaton and porosty, ntal ol saturaton and porosty are the two man factors of geology whch nfluence well productvty. Wth the ncrease of ntal ol saturaton and porosty, well productvty ncreases. Fg.2 and Fg.3 are ntal ol saturaton dstrbuton and porosty dstrbuton n the man reservor at a part of Chang 7 reservor. From green to red, the darker the color s, the greater the value s. Fg.2 Dstrbuton of ntal ol saturaton n the tght reservor The enrchment zone s the area of hgh ol saturaton and hgh porosty. Based on Fg.2 and Fg.3, some enrchment zones have been selected. Producton data of 4 wells n the enrchment zones and 3 wells outsde the enrchment zones are compared (table 4). Result shows that average well producton of 4 wells s 11.88m 3 /d n enrchment zones, average producton of the other 3 wells s 6.43m 3 /d. Well producton of enrchment zone s hgher than that n the non-rch regon, t shows that the method s accurate and feasble. 638

5 Fgure 3 Dstrbuton of porosty n the tght reservor Table 4 Comparson of enrchment zone and non-rch zone Zone enrchment zone non-rch zone Well Name H L K So M Qo Qava /m /m /md /% /m 3 /m 3 /m 3 An An An An An An An Where, Qava average producton. CONCLUSION (1) It analyses the nfluencng factors of well productvty by usng gray correlatve method. Results show that effects on well productvty from hgh to low are: sand volume, ntal ol saturaton, resstvty, nterval transt tme, porosty, perforaton length, permeablty and formaton thckness. The massve fracturng and preferred regon wth hgh ol saturaton wll greatly mprove well productvty n Chang 7 tght-ol reservor n Ordos Basn. (2) The enrchment zone s selected by usng the result of gray correlatve analyss at the part of Chang 7 reservor. The average well producton of 4 wells s 11.88m 3 /d n enrchment zone, the average well producton of the other 3 wells n non-rch regon s 6.43m 3 /d. (3) It s convenent and requres less samples to use gray correlatve method for analyzng factors of well productvty n tght reservors. The results can reflect the relatonshp between characterstc parameters and well productvty. It s of great sgnfcance to optmze development regon and reduce the nvestment rsk n tght reservors. REFERENCES [1] Zhao Zhengzhang, Du Jnhu, Zou Caneng, et al. Tght ol & gas. Petroleum Industry Press. 2012; [2] Zou Caneng, Zhu Ruka, Wu Songtao, et al. Acta Petrole Snca, 2012,33(2): [3] Du Jnhu, He Haqng, L Janzhong, et al. Chna Petroleum Exploraton, 2014,19(1):1-9. [4] Dong Wenjn, Lu jn, Dng Janl, et al. Tsnghua Unversty Press, 2010; [5] Lu Hu, Yuan Xuefang, Zhou Lzh, et al. Drllng & Producton technology, 2013,36(1): [6] Tang Merong, Zhao Zhenfeng, L Xanwen, et al. Drllng & Producton Technology, 2010,32(2): [7] Wang Wendong, Su Yulang, Mu Ljun, et al. Journal of Chna Unversty of Petroleum, 2013,37(3): [8] Lang Tao, Chang Yuwen, Guo Xaofe, et al. Petroleum Exploraton and Development, 2013,40(3): [9] Xu Janhong. Journal of Southwest Petroleum Unversty(Scence & Technology Edton),2012,34(2): [10] Ln Senhu, Zou Caneng, Yuan Xuanjun, et al. Lthologc Reservors,2011,34(4): [11] Feng Shengbn, Nu Xaobn, Lu Fe, et al. Journal of Central South Unversty(Scence and Technology),2013, 44(11): [12] Zou Caneng, Yang Zh, Tao Shzhen, et al. Petroleum Exploraton and Development, 2012,39(1):