• CN 62-1091/P
• ISSN 1001-8166
• 月刊 创刊于1986年

Optimization of the Rock Physical Model in Tight Sandstone Reservoir

1.西北大学地质学系,二氧化碳捕集与封存技术国家地方联合工程研究中心,陕西 西安 710069
2.中煤科工集团西安研究院有限公司,陕西 西安 710077
3.中国石油长庆油田公司勘探开发研究院,陕西 西安 710018
Jia Lingyun1,, Li Lin1, Wang Qianyao2, Ma Jinfeng1, Wang Daxing3
1.National & Local Joint Engineering Research Center of Carbon Capture and Storage Technology, Department of Geology of Northwest University, Xi’an 710069, China;
2.China Coal Technology Engineering Group Xi’an Research Institute, Xi’an 710077, China;
3.Research Institute of Exploration and Development, Changqing Oil Field Company, PetroChina, Xi’an 710018,China;
引用本文:

Jia Lingyun, Li Lin, Wang Qianyao, Ma Jinfeng, Wang Daxing. Optimization of the Rock Physical Model in Tight Sandstone Reservoir[J]. Advances in Earth Science, 2018, 33(4): 416-424, doi:10.11867/j.issn.1001-8166.2018.04.0416

Krief模型、Nur模型和Pride-Lee模型通常被用于计算砂岩储层干岩石模量,但对于致密砂岩储层却效果不佳。基于Krief模型和Nur模型,在满足纵波或横波预测值与实测值差值最小的条件下,通过Gassmann方程求出模型中的岩性指数m或临界孔隙度Øc,进而将模型中通常采用的经验参数表示成随采样点变化的值,提高了Krief模型和Nur模型估算纵横波速的精度,称为变参数Krief模型和变参数Nur模型。此外,对比不同约束条件下纵横波预测精度,可知在致密砂岩储层中3种模型的剪切模量公式的精度更高、适用性更好。Han提出的Kdryudry关系式不受孔隙度、岩性等因素的影响,将该关系式与上述3种模型中任意一种剪切模量公式结合建立干岩石模型,应用到Gassmann方程中对鄂尔多斯盆地苏里格气藏盒8致密砂岩储层横波速度进行预测,提高了预测横波速度的精度,同时获得了3种模型中每个采样点对应的岩性指数m、临界孔隙度Øc和固结参数c的值,这些参数值可以反映出储层的岩性差异、孔隙结构、压实程度等特征,映射了储层的地质特征。

Abstract:

Krief model, Nur model and Pride-Lee model are usually used to calculate dry rock modulus of sandstone reservoirs, but they are not effective for tight sandstone reservoirs. Based on Krief model and Nur model, and minimizing the difference between predicted P-wave or S-wave velocities and measured velocities, we acquireed lithologic index m in Krief model and critical porosity Øc in Nur model by Gassmann relationship. The empirical parameters used in the models are expressed as the values changing with depth, so the accuracy of Krief and Nur models to estimate the P-wave and S-wave velocities was improved, and these two models are called as the variable parameter Krief model and the variable parameter Nur model. In addition, comparing with prediction accuracy of P-wave and S-wave velocities under different constraints, we can see that the shear modulus formulas in the three models are more accurate and more suitable in the tight sandstone reservoir. Han’s relationship about Kdry and udry is not affected by porosity, lithology and other factors, and the paper established dry rock model by Han’s relationship and any one of the above three models. The new dry rock model was applied in the Gassmann relationship to predict S-wave velocity of H8 tight sandstone reservoir in Sulige Gas Filed, Ordos Basin, which improved the accuracy of predicting S-wave velocity. At the same time, lithology index m in Krief model, critical porosity Øc in Nur model and consolidation parameters c in Pride-Lee model which are corresponding to each sample can be obtained. The values of these parameters can reflect lithology difference, pore structure, compaction degree and other characteristics, which indicate the geological characteristics of the reservoir.

Key words: Tight sandstone reservoir ; Bulk modulus ; Rock physical model ; The relationship of Kdry and udry.
1 引 言

2 岩石物理模型

2.1 3种常用岩石物理模型

Gassmann孔隙介质理论中,干岩石模量是不确定的,通常采用实验室测量和理论预测的方法,实验室测量数据一般较少甚至缺乏,常用的方法是通过干岩石模量与基质模量的关系进行预测。为了获得这种关系,前人提出了一些干岩石模型,如Krief模型、Nur模型和Pride模型等。每一种模型都有其应用前提及实用性。

Krief等[8]认为干岩石的纵横波速度比与孔隙度无关,但与基质的纵横波速度比相等,将Raymer等[17]实验获得的砂岩数据拟合为一个关于Biot系数β的表达式:

$K dry = K 0 ( 1 - β ) ,$ （1）

$u dry = u 0 ( 1 - β ) ,$ (2)

$K dry = K 0 ( 1 - Ø ) m ( Ø ) ,$ （3）

$u dry = u 0 ( 1 - Ø ) m ( Ø ) ,$ (4)

Nur等[11]认为大部分岩石都有一个临界孔隙度,用Øc表示,当Biot系数β=Ø/Øc时,上述干岩石模型称为临界孔隙度模型,孔隙度满足0<Ø<Øc,当岩石的孔隙度超过临界孔隙度时,即Ø>Øc,岩石矿物颗粒会相互分离,处于悬浮状态。Nur模型的具体公式为[11]:

$K dry = K 0 ( 1 - Ø / Ø c ) ,$ （5）

$u dry = u 0 ( 1 - Ø / Ø c ) ,$ (6)

Pride[12]引入固结参数c,将干岩石模量简化为:

$K dry = K 0 1 - Ø 1 + cØ ,$ （7）

$u dry = u 0 1 - Ø 1 + 1.5 cØ ,$ (8)

$u dry = u 0 1 - Ø 1 + γc Ø ,$ (9)

2.2 Krief和Nur模型优化

Krief模型与张金钟[18,19]提出的地层因数公式Vp=Vm(1-Ø)x形式类似,其中VpVm为岩石和基质的纵波速度,x被称为岩性指数,张金钟对美国岩心分析家协会公布的实验数据和Han等[20]的实验数据进行研究,发现指数x值与孔隙度、压力、温度和泥质含量有关。本文将Krief模型中的m也称为岩性指数,并认为指数mx的变化规律类似,也与孔隙度、压力、温度和泥质含量等因素有关。m值一般分布范围为010[21],由于致密砂岩储层地质特征的特殊性,使得影响m值的因素更为复杂,因此认为m值是一个多因素综合的变量。

Nur等[11]通过实验数据获得了多种常用纯矿物岩石的临界孔隙度值,指出临界孔隙度的大小取决于岩石的岩性及内部结构,并发现裂隙的存在会导致岩石有一个很低的临界孔隙度。Blangy等[22]通过研究Yin等[23]和Han等[20]的数据指出沉积砂岩临界孔隙度随着泥质含量的多少变化。张佳佳等[16]指出岩石的临界孔隙度是孔隙形状的函数。因此,可知临界孔隙度是与岩石成分、孔隙形状、胶结程度和裂隙发育程度等多种因素有关的物理量。临界孔隙度Øc分布范围为01。

2.3 采用Han关系式优化岩石物理模型

Knackstedt等[14]研究发现Krief和Nur剪切模量公式的精度较高,而体积模量公式误差相对较大,针对致密砂岩储层的复杂地质特征,需要建立更精确的岩石物理模型才能达到储层预测的要求。许多学者研究发现纯砂岩的干岩石纵横波速度比(Vp/Vs)dry是一个固定值[21,24,25],根据Gassmann方程可推出干岩石体积模量Kdry和剪切模量udry的比值Kdry/udry=(Vp/Vs $) dry 2$ -4/3,也是一个固定值。Han[26]通过大量实验数据研究提出某一个采样点的体积模量和剪切模量比Kdry/udry随孔隙度、有效压力和基质性质的变化接近一个固定值,但不同采样点的Kdry/udry值不同,主要因为其与岩石的结构有关,并证实干岩石的体积模量和剪切模量有非常好的相关性,这个相关性对纯砂岩、泥质砂岩、不胶结或胶结的砂岩都实用,其受压力的影响较小,不予考虑。本文采用研究区获得的Kdryudry数据对Han公式[26]重新拟合,具体公式为:

$M dry = ρ dry V p_ dry 2 = K dry + 4 / 3 u dry ,$ （10）

$u dry = 0.0009 × M dry 2 + 0.3186 × M dry + 1.6888 ,$ (11)

(1)采用Voigt-Reuss-Hill模型计算岩石基质的剪切模量u0

(2)采用Brie经验公式计算流体的体积模量,其中各相流体的体积模量采用Batzle等[27]方程计算。

(3)在变参数Krief模型、变参数Nur模型或Pride-Lee模型中,选取任意一个剪切模量公式,将其与 Han[26]提出的Kdryudry关系式相结合,计算出干岩石的体积模量和剪切模量。

(4)将干岩石模量应用到Gassmann方程中,在预测纵波速度和实测纵波速度相比误差最小约束条件下,计算出岩性指数m值、临界孔隙度Øc值或胶结参数c值,再根据udry=usat=ρ $V s 2$ 预测出横波速度,其中usat为饱和岩石剪切模量;ρ为岩石密度;Vs为横波速度。

3 模型的应用

3.1 变参数模型的应用

Fig.1

Comparison of predicted P-wave velocity

Fig.2

Comparison of predicted S-wave velocity

Fig.3

Cross plot of lithological index and porosity

Fig.4

Cross plot of critical porosity and porosity

Fig.5

Cross plot of consolidation parameters and porosity

Fig.6

Comparison of predicted S-wave velocity

3.2 采用Han关系优化模型的应用

Fig.7

Comparison of predicted P-wave velocity

Fig.8

Comparison of predicted S-wave velocity

Fig.9

Cross plot of lithological index and porosity

Fig.10

Cross plot of critical porosity Øc and porosity

Fig.11

Cross plot of consolidation parameters and porosity

Fig.12

Comparison of prediction velocity methods of He 8 formation of well Su 46

4 结 论

Han虽在多种砂岩岩样的基础上提出了Kdryudry关系式,但直接应用到不同的研究区中可能会有一定的误差。在实际应用中,需要根据研究区的数据重新拟合,修改公式中的系数值,获得更准确的拟合公式。

The authors have declared that no competing interests exist.

 [1] [邹才能,陶士振,侯连华,等. 非常规油气地质[M]. 北京:地质出版社, 2011.] Zou Caineng, Tao Shizhen, Hou Lianhua, et al.Unconventional Oil and Gas Geology[M]. Beijing: Geological Publishing House, 2011. [本文引用: 1] [2] [毛克宇. 梨树断陷营城组致密砂岩测井流体识别方法及其适应性分析[J]. 地球科学进展, 2016, 31(10):1 056-1 066.] Mao Keyu.Logs fluid typing methods and adaptive analysis of tight sandstone reservoir of Yingcheng formation in Lishu Fault[J]. Advances in Earth Science, 2016, 31(10):1 056-1 066. URL 致密砂岩储层具有低孔隙度、低渗透率的特征,储层中的流体对测井响应的贡献大大减小,流体识别及评价变得更加困难,迫切需要发展有效的测井解释方法。从梨树断陷营城组致密碎屑岩储层的地质特征研究入手,基于孔隙流体对测井数据的敏感性研究了测井曲线重叠法、声波测井与反演声波曲线重叠法、孔隙度差值与比值法、电阻率—孔隙度交会图法、正态分布法等多种流体识别方法,建立并优选了有效的测井流体评价方法,实现了对研究区油气层的定性识别。研究表明,上述方法均适用于研究区的流体识别,2种重叠法、孔隙度差值与比值法、电阻率—孔隙度交会图法更适用于天然气储层,孔隙度差值与比值法、电阻率—孔隙度交会图法、正态分布法更适用于油水储集层。利用上述方法对研究区目标井进行了测井资料精细解释,重新认识和评价储层,为油田勘探开发提供重要的决策依据与参考。 [本文引用: 1] [3] Gassmann F.Elastic waves through a packing of spheres[J]. Geophysics, 1951, 16(3): 673-682. [本文引用: 1] [4] [杨扬,马劲风,李琳. CO2地质封存四维多分量地震监测技术进展[J]. 地球科学进展, 2015, 30(10): 1 119-1 126.] Yang Yang, Ma Jinfeng, Li Lin.Research progress of carbon dioxide capture and storage technique and 4D seismic monitoring technique[J]. Advances in Earth Science, 2015, 30(10): 1 119-1 126. URL CCS技术是目前公认的快速减缓温室效应的最有效方法,CO2地质封存是CCS技术最核心的问题之一,监测CO2地质封存的安全性贯穿于CO2注入过程中与封存以后。四维地震监测技术是监测CO2是否泄、证实CO2封存安全性最有效的技术手段。常规四维地震技术通过对比CO2注入前后及注入不同阶段2次或者多次三维地震纵波振幅差异与旅行时差异,确定CO2在地下分布。而纵波振幅或旅行时差异是CO2饱和度与孔隙压力的综合反映,单纯的纵波信息难以区分饱和度与压力信息。目前,四维多分量地震监测技术的潜力并未挖掘,由于横波速度对于压力敏感,利用四维转换波信息监测CO2地质封存,可以识别注入CO2的压力分布范围。对于各向异性介质的储层,对比一次地震观测PS1,PS2旅行时、振幅差异与2次地震采集之间PS1,PS2旅行时、振幅差异,还可以有效确定注入CO2前与注入期间储层裂隙、裂缝的变化,以及储层与盖层的应力状态。四维多分量地震资料结合岩石物理资料和全波列测井资料,可以更准确地确定可能的CO2泄风险区域,更加可靠地评估CO2地质封存的安全性。 [本文引用: 1] [5] [汪鹏,钟广法.南海ODP1144站深海沉积牵引体的岩石物理模型研究[J]. 地球科学进展, 2012, 27(3): 359-366.] Wang Peng, Zhong Guangfa.Application of rock physics models to the deep-sea sediment drift at ODP site 1144, northern South China Sea[J]. Advances in Earth Science, 2012, 27(3): 359-366. Magsci URL

ODP1144站是南海唯一钻揭深海沉积牵引体的站位，其完整的岩芯和测井资料为开展该沉积牵引体的岩石物理模型研究提供了良好的基础。此项研究对于理解南海深海沉积物中岩性参数与弹性参数间的关系具有重要意义,并可为根据反射地震资料开展定量岩性参数预测提供依据。对现有的深海沉积物岩石物理模型包括Wood悬浮模型、等球体颗粒接触模型、Sun速度—孔隙度关系模型进行了综述。根据岩芯分析资料将1144站深海沉积物的矿物组分简化为粘土矿物、碳酸盐、陆源碎屑和硅质生物4类；其中后3种组分的弹性模量及密度值分别由其代表矿物——方解石、石英及蛋白石的理论值代替，粘土矿物组分的等效弹性模量和等效密度则分别由Voigt-Reuss-Hill平均和体积平均计算得出。将3种岩石物理模型应用于1144站，计算得出深海沉积物的纵波速度并将其与声波测井纵波速度进行比较。结果表明，Sun模型计算结果与实测结果的吻合最好,误差最小；Wood模型所得结果在浅层与实测结果较吻合，在深层与实测结果出现偏差，误差较小；而等球体颗粒接触模型计算结果整体偏高，误差较大。

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The Raymer equation is the best of the velocity-porosity models for the water-saturated systems. Gassmann's relations are shown to accurately map between the dry and fluid-saturated states. Based on these results, we propose a new empirical method, based solely on a knowledge of the mineral modulus, to estimate the full velocity-porosity relationship for monomineralic consolidated sands under dry and fluid-saturated states. The method uses the equation of Krief et al. for the dry shear modulus and the empirical equation of Arns et al. for the dry Poisson's ratio. Gassmann's relations are applied to obtain the fluid-saturated states. The agreement between the new empirical method, the numerical data and available experimental data for dry and water-saturated states is encouraging. [本文引用: 2] [15] Arns C H, Knackstedt M A, Pinczewski W V, et al. Computation of linear elastic properties from microtomographic images: Methodology and agreement between theory and experiment[J]. Geophysics, 2002, 67(5):1 396-1 405. URL ABSTRACT Elastic property-porosity relationships are derived directly from microtomographic images. This is illustrated for a suite of four samples of Fontainebleau sandstone with porosities ranging from 7.5% to 22%. A finite-element method is used to derive the elastic properties of digitized images. By estimating and minimizing several sources of numerical error, very accurate predictions of properties are derived in excellent agreement with experimental measurements over a wide range of the porosity. We consider the elastic properties of the digitized images under dry, water-saturated, and oil-saturated conditions. The observed change in the elastic properties due to fluid substitution is in excellent agreement with the exact Gassmann's equations. This shows both the accuracy and the feasibility of combining microtomographic images with elastic calculations to accurately predict petrophysical properties of individual rock morphologies. We compare the numerical predictions to various empirical, effective medium and rigorous approximations used to relate the elastic properties of rocks to porosity under different saturation conditions. [本文引用: 1] [16] [张佳佳,李宏兵,刘怀山,等.几种岩石骨架模型的适用性研究[J].地球物理学进展,2010, 25(5): 1 697-1 702.] Zhang Jiajia, Li Hongbing, Liu Huaishan, et al. Accuracy of dry frame models in the study of rock physics[J]. Progress in Geophysics, 2010, 25(5): 1 697-1 702. URL 在地震岩石物理中,Biot-Gassmann理论通常用来研究饱和流体对岩石地震特征的影响以及描述地震响应与岩石物性之间的关系.然而Biot-Gassmann理论并没有阐述多孔岩石的骨架与基质之间的关系,因此出现了各种各样的岩石骨架模型分别从不同的角度建立了岩石骨架与岩石基质之间的关系,如Krief模型、Nur模型(临界孔隙度模型)和Pride模型等都是广泛使用的岩石骨架模型.本文将这些常见的岩石骨架模型应用于Biot-Gassmann理论中,进行理论模型正演、速度预测以及Biot系数计算等,并与实验室测量数据对比,分析发现Pride模型比Krief模型和Nur模型的适用范围更广,以及Krief模型和Nur模型不能适用于低压、低孔岩石的特点. [本文引用: 2] [17] Raymer L L, Hunt E R, Gardner J S.An improved sonic transit time to porosity transform[C]∥Transactions of the SPWLA 21st Annual Logging Symposium, 1980: 1-13. [本文引用: 1] [18] [张金钟. 声波地层因素公式的物理基础及其简化形式[C]∥全国第三届测井年会论文,1988.] Zhang Jinzhong.The physical basis and simplified form of the acoustic formation factor formula[C]∥Third Annual Logging Conference, 1988. [本文引用: 1] [19] [张金钟. 多孔地层的骨架岩性指数和孔隙结构指数[J].西安石油学院学报,1989,4(4):1-8.] Zhang Jinzhong.Matrix lithology exponent of porous formation versus porosity exponent[J]. Journal of Xi’an Shiyou University, 1989, 4(4): 1-8. [本文引用: 1] [20] Han D H, Nur A.Effects of porosity and clay content on wave velocities in sandstones[J]. Geophysics, 1986, (51):2 093-2 107. [本文引用: 2] [21] Brie A, Pampuri F, Marsala A F, et al. Shear sonic interpretation in gas-bearing sands[C]∥SPE Annual Technical Conference and Exhibition. Dallas, Texas: SPE. 1995: 701-710. [本文引用: 2] [22] Blangy J P, Strandenes S, Moos D, et al. Ultrasonic velocities in sands- revisited[J]. Geophysics, 1993, 58(3): 344-356. [本文引用: 1] [23] Yin H, Han D H, Nur A.Study of Velocities and Compaction on Sand-clay Mixture[R]. S. R. B. Report, Stanford University, 1988: 33. [本文引用: 1] [24] Pickett G R.Acoustic character log and their application in formation evaluation[J]. Journal of Petroleum Technology, 1963, 15(6): 659-667. DOI:10.2118/452-PA URL Examples are presented which show that the velocity, amplitude, attenuation and apparent frequency of several acoustic waves can be recorded in the borehole. Examination of such recordings, termed "character" logs, indicates that the wave types observed include a refracted compressional wave and a wave which travels with formation shear velocity. Laboratory data are used to show that compressional and shear wave velocities are dependent on porosity, effective stress and lithology; but that the change in reciprocal velocity per unit change in porosity is larger for shear waves than for compressional waves. We, therefore, conclude that the accuracy of porosity determinations can sometimes be improved by use of shear wave velocities, provided that the shear wave amplitudes are large enough to delineate the shear arrival from the preceding compressional arrival on the character log. Borehole data are presented which show that the difference between shear wave and compressional wave reciprocal velocities can be used to predict porosities. This is a refinement which may allow the prediction of porosities from single-receiver acoustic logs without introduction of errors from borehole fluid travel-times. Laboratory and field data are presented to show that the relationship between compressional and shear wave velocities can be used to indicate lithology. An example is presented to show that fractures usually cause a greater reduction in borehole shear wave amplitudes than in compressional wave amplitudes, an effect which may offer a more reliable means of detecting fractures. The complexity of the borehole acoustic wave train can make presently available cement bond logs highly sensitive to the gate and bias settings used. The character log offers a means to circumvent possible misinterpretations by recording all amplitudes, from which the interpreter can select the appropriate data for evaluating the cement bond. Character logs may also be used as a quality control for open-hole transit-time logs when existence of small compressional wave amplitudes interferes with the proper functioning of bias-controlled timing devices. Evaluation of the potential uses of character log data is not complete; but a character log presented in a form convenient for routine use would be a desirable addition to currently available logs. To summarize, possible applications for such a log in formation evaluation include the following (1) quality control of transit-time logs, (2) refinement of porosity predictions, (3) determination of lithology, (4) improvement of fracture detection and (5) improvement of cement bond evaluation. Suggestions are made regarding the requirements for a sufficient but practical character log for routine use. [本文引用: 1] [25] Murphy W F, Schwartz L M, Hornby B.Interpretation physics of Vp and Vs in sedimentary rocks[C]∥Transactions SPWLA 32nd Annual Logging Symposium, 1991: 1-24. [本文引用: 1] [26] Han D H.Estimate shear velocity based on dry P-wave and shear modulus relationship[C]∥SEG Int’l Exposition and 74th Annual Meeting, 2004: 10-15. [本文引用: 3] [27] Batzle M, Wang Z.Seismic properties of pore fluids[J]. Geophysics, 1992, 57(1):1 396-1 468. [本文引用: 1] [28] [王大兴. 致密砂岩气储层的岩石物理模型研究[J].地球物理学报,2016,59(12): 4 603-4 622.] Wang Daxing.Study on the rock physics model of gas reservoirs in tight sandstone[J]. Chinese Journal of Geophysics, 2016, 59(12): 4 603-4 622. URL 根据鄂尔多斯盆地苏里格气田以往实测和新测的共17口井51块岩样超声波实验数据,得到304组不同孔隙度和不同含水饱和度下对应的纵横波速度、泊松比等弹性参数.重新优选计算体积模量和泊松比与含气饱和度的关系,表明苏里格气田上古生界二叠系石盒子组盒8致密砂岩储层的模型与Brie模型(e=2)相似度最高.由此建立的苏里格气田储层岩石物理模型,更好的表征了致密岩石储层物理参数随含气饱和度变化规律,为该区储层预测提供了理论依据.致密储层岩石物理模型研究成果应用于苏里格气田多波地震资料气水预测中,实际例子表明该模型适用于该区的储层和含气性预测,并取得了较好的效果. [本文引用: 1] [29] [付斌,李进步,陈龙,等. 苏里格气田西区致密砂岩气水识别方法与应用[J]. 特种油气藏,2014,21(3):66-69.] Fu Bin, Lin Jinbu, Chen Long, et al. The gas/water identification method and its application in tight sandstone reservoir in the west of sulige gas field[J]. Special Oil and Gas Reservoirs, 2014, 21(3): 66-69. Magsci URL 在前人研究工作的基础上，在苏里格气田西区筛选多口典型井，采用阵列感应及偶极子声波实验，获得了岩石物理参数，明确了电性特征与气水间的关系，建立了对应的交会图，并应用在三维高分辨率地震资料的解释上。基于地震、测井联合技术，预测了苏１８６ 区块气水分布特征，有效地指导了井位部署与气藏开发，同时对其他致密砂岩气藏的气水分布识别具有一定的指导意义。 [本文引用: 1] [30] [贾培锋,杨正明,肖前华,等. 致密油藏储层综合评价新方法[J]. 特种油气藏,2015,22(4): 33-36.] Jia Peifeng, Yang Zhengming, Xiao Qianhua, et al. A new method to evaluate tight oil reservoirs[J]. Special Oil and Gas Reservoirs, 2015,22(4): 33-36. Magsci URL 致密油藏开发需要储层评价作为指导，但尚无一套评价方法立足于致密油开发实际。通过对大庆油田和长庆油田典型致密油储层岩心进行实验研究，运用统计学方法和数值模拟方法，优选了平均喉道半径、可动流体百分数、脆性指数、地层压力系数、启动压力梯度、原油黏度６ 个参数用于致密储层评价。在低渗透油藏参数评价界限基础上，补充了地层压力系数和脆性指数分类界限；提出了致密油储层综合分类评价方法，将致密储层按综合分类系数分为４类。应用结果表明，大庆油田龙西区块的扶余油层和高台子油层，长庆油田的长８、长９ 储层为Ⅱ—Ⅲ类储层，有一定开发潜力。 [本文引用: 1] [31] Li Lin, Ma Jinfeng.Study of shear wave velocity prediction during CO2-EOR and sequestration in Gao 89 area of Shengli Oilfield[J]. Applied Geophysics, 2017,14(3): 372-380. URL Shear-wave velocity is a key parameter for calibrating monitoring time-lapse 4D seismic data during CO2-EOR (Enhanced Oil Recovery) and CO2 sequestration.However,actual S-wave velocity data are lacking,especially in 4D data for CO2 sequestration because wells are closed after the CO2 injection and seismic monitoring is continued but no well log data are acquired.When CO2 is injected into a reservoir,the pressure and saturation of the reservoirs change as well as the elastic parameters of the reservoir rocks.We propose a method to predict the S-wave velocity in reservoirs at different pressures and porosities based on the Hertz-Mindlin and Gassmann equations.Because the coordination number is unknown in the Hertz-Mindlin equation,we propose a new method to predict it.Thus,we use data at different CO2 injection stages in the Gao89 well block,Shengli Oilfield.First,the sand and mud beds are separated based on the structural characteristics of the thin sand beds and then the S-wave velocity as a function of reservoir pressure and porosity is calculated.Finally,synthetic seismic seismograms are generated based on the predicted P-and S-wave velocities at different stages of CO2 injection. 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