Seismic-Derived Rock True Resistivity (R) Revisited. Part I: Reformulation Of Combined Gassmann – Shaly Sand Models

B. Widarsono, Merkurius F Mendrofa
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Abstract

The last decade has observed frantic efforts by geoscientists to extract as much information as possible from seismic data. From the traditional role of establishing subsurface structural geometry, seismic processing and interpretations have evolved into an ever increasing role in providing rock physical properties such as acoustic impedance (AI) and porosity (0). The more common use of 3-D seismic surveys, in both exploration and development stages, have fur- ther underlined the role of seismic data as provider of inter-well rock property data. Further developments in the petrophysics-related seismic interpretation have also shown efforts to ex- tract information related to contents of formation rocks. From the widely acknowledged brightspot analysis for detecting presence of gas-bearing porous rocks in the last decades of the 20 century to the later efforts to extract information regarding fluid saturation in reservoir. Actually, as early as in mid- 1960s have scientists started to investigate the relations between acoustic signals and fluid saturation (e.g King, 1966; Domenico, 1976; Gregory, 1976). However, due to the fact that the then commonly used of 2-D seismic was considered as having insuf- ficient resolution for any practical uses in the field, the efforts remained mainly for academic purposes only. Rapid developments in technology of 3-D seis- mic survey and processing, as well as its more com- mon use at present have prompted attentions back to the investigations aimed at extracting fluid saturation information from seismie data. In 1990s have Widarsono and Saptono (1997) started a series of investigation through laboratory measurements and modeling using core samples. This was followed by more works not only at laboratory level but at larger levels of well and field scales (e.g. Widarsono Saptono, 2000a, 2000b, and 2001; and Widarsono et al, 2002a, 2000b). Other investigators (e.g. Furre Brevik, 2000; Wu, 2000; Zhu et al, 2000; and more recently Wu et al, 2005) have also devoted some works to achieving the same goal. Other paths of development have incorporated other supporting tech- niques such as non-linear regression (e.g.Balch et al, 1998) and artificial neural network (e.g. Poupon Ingram, 1999; Oldenziel et al, 2000).From various investigations using seismic waves as the sole data for fluid saturation extraction, short- comings were soon felt in the form of 'narrow bands' of acoustic signals (ie P-wave velocity, V, and acoustic impedance, AI) that are influenced by varia- tions in fluid saturation. In other words, V, and AI are not too influenced by variation in fluid saturation. This reduces the effectiveness of seismic-derived V and Al as fluid saturation indicators. Efforts were then devoted to link V, and AI to other parameters such as rock true resistivity (R), a parameter known to be very sensitive to variation in fluid saturation. Widarsono and Saptono (2003, 2004) provide laboratory verifications and first field trial with some degree of succes. However, certain assump- tions (i.e. constant/uniform porosity) in the theoreti- cal formulation were still adopted in the above works, which in turn reduced the validity of the resulting formula produced and used. In this paper, the first part of a three-part work, is devoted to reformulating the combination of Gassmann theory and shaly sand water saturation models of Poupon and Hossin. These are to replace the shale-free Archie model used in the above works, which is considered as invalid for most field uses. With this reformulation, it is hoped that a more robust model/formula of resistivity as a function of acoustic impedance (R, = fAI)) is achieved, hence a more reliable resistivity could be extracted from seismic- derived acoustic impedance. Summarily, the objectives of the works a part of them presented in this paper are - To establish a model/method to obtain formation rock true resistivity (R) from seismic-derived acoustic impedance (AI), and To provide correction/modification onto previous works reported in Widarsono Saptono (2003, 2004).
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地震源岩石真电阻率(R)重新研究。第一部分:重新制定联合Gassmann -页岩砂模型
在过去的十年里,地球科学家们疯狂地从地震数据中提取尽可能多的信息。从建立地下结构几何的传统作用,地震处理和解释在提供岩石物理性质(如声阻抗(AI)和孔隙度(0))方面的作用越来越大。在勘探和开发阶段,三维地震调查的应用越来越普遍,这进一步强调了地震数据作为井间岩石性质数据的提供者的作用。与岩石物理有关的地震解释的进一步发展也显示出提取与地层岩石含量有关的信息的努力。从20世纪最后几十年被广泛认可的用于检测含气多孔岩石存在的亮点分析,到后来用于提取储层流体饱和度信息的努力。实际上,早在20世纪60年代中期,科学家们就开始研究声信号与流体饱和度之间的关系(如King, 1966;多梅尼科,1976;格里高利,1976)。然而,由于当时普遍使用的二维地震被认为在现场的任何实际应用中具有不足的分辨率,因此这些努力仍然主要用于学术目的。随着三维地震测量与处理技术的迅速发展和日益普遍的应用,从地震资料中提取流体饱和度信息的研究又重新受到重视。在20世纪90年代,Widarsono和Saptono(1997)通过实验室测量和使用岩心样本建模开始了一系列的调查。随后,不仅在实验室水平,而且在更大的井和现场规模上进行了更多的工作(例如,Widarsono Saptono, 2000a, 2000b和2001;和Widarsono等人,2002a, 2000b)。其他研究者(如Furre Brevik, 2000;吴,2000;Zhu et al ., 2000;最近Wu et al, 2005)也投入了一些工作来实现同样的目标。其他的发展路径包含了其他支持技术,如非线性回归(如balch等人,1998年)和人工神经网络(如Poupon Ingram, 1999年;Oldenziel et al, 2000)。从使用地震波作为流体饱和度提取的唯一数据的各种研究中,很快就发现了受流体饱和度变化影响的声信号(即p波速度,V和声阻抗,AI)的“窄带”形式的缺点。也就是说,V和AI不受流体饱和度变化的太大影响。这降低了地震导出的V和Al作为流体饱和度指标的有效性。然后致力于将V和AI与其他参数联系起来,例如岩石真电阻率(R),该参数对流体饱和度的变化非常敏感。Widarsono和Saptono(2003,2004)提供了实验室验证和首次现场试验,并取得了一定程度的成功。然而,上述工作仍然采用了理论公式中的某些假设(即恒定/均匀孔隙率),这反过来又降低了生成和使用的所得公式的有效性。本文是由三部分组成的工作的第一部分,致力于重新制定Gassmann理论与Poupon和Hossin页岩砂水饱和度模型的结合。这些模型将取代上述工作中使用的无页岩的Archie模型,该模型被认为对大多数现场应用无效。通过这种重新表述,希望得到一个更稳健的电阻率作为声阻抗函数(R, = fAI)的模型/公式,从而可以从地震声阻抗中提取更可靠的电阻率。综上所述,本文提出的部分工作的目标是建立一种从地震声阻抗(AI)获得地层岩石真电阻率(R)的模型/方法,并对Widarsono Saptono(2003,2004)中报道的先前工作进行修正/修改。
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