骨架导电的混合泥质砂岩通用孔隙结合电阻率模型研究

在水介质中顺序添加分散粘土颗粒、油珠、导电骨架颗粒、层状泥质,并对每一种成分进行连续积分,建立了一种适用骨架导电及含有分散粘土和层状泥质的泥质砂岩通用电阻率模型.通过对该模型的影响因素分析,发现泥质分布形式对模型计算的含水饱和度有很大影响;对应两个不同粘土颗粒电阻率或骨架颗粒电阻率的地层电导率之差,几乎与总含水饱和度无关,而对应两个不同层状泥质电阻率的地层电导率之差,随总含水饱和度增大而增大;骨架胶结指数变化对地层电导率与总含水饱和度关系曲线的影响最大,而粘土胶结指数变化对地层电导率与总含水饱和度关系曲线的影响最小;饱和度指数对地层电导率与总含水饱和度关系曲线的影响随总含水饱和度的增大而减小.通过一组骨架导电的人造岩样的试验,表明当地层水电阻率.小于颗粒电阻率时,该模型可以用于不含粘土的骨架导电的岩石.通过两组分散泥质砂岩岩样实验测量数据和一组层状泥质砂岩测井资料及实际测井资料的计算,表明本文给出的电阻率模型既适用于分散泥质砂岩地层解释又适用于层状泥质砂岩地层解释,同时,还适用于含有分散粘土和层状泥质的混合泥质砂岩地层解释.     

基于差分方程和通用阿尔奇方程的含黄铁矿混合泥质砂岩电阻率模型

针对现有导电模型很难描述含黄铁矿混合泥质砂岩储层导电规律的难题,本文设计并压制了黄铁矿骨架纯岩样,以及不同分散泥质、层状泥质和黄铁矿含量的石英骨架人造岩样,测量了岩样岩电及配套实验数据,从实验角度分析了黄铁矿含量变化对岩石导电性的影响。考虑到岩石中不同物质成分间导电特性的差异,提出将含黄铁矿混合泥质砂岩分为层状泥质、石英颗粒、黄铁矿颗粒、油气、分散粘土颗粒、微孔隙水和可动水,将电导率差分方程与通用阿尔奇方程相结合,利用电导率差分方程描述在主介质中添加分散相介质的导电规律,而利用通用阿尔奇方程描述两种导电介质组成的混合介质的导电规律,在此基础上利用并联导电理论描述分散泥质砂岩与层状泥质的导电规律,建立了一种能够有效描述含黄铁矿混合泥质砂岩导电特性的新型通用电阻率模型。理论验证表明所建立的电阻率模型满足物理约束条件,且预测的导电规律与实验规律相一致,即随着黄铁矿颗粒含量和电导率的增加,R_t和I值均减小。利用实验测量的46块人造岩样在不同含油饱和度下的岩电实验数据,验证了该模型完全能够描述黄铁矿骨架纯岩样、石英骨架混合泥质砂岩岩样,以及骨架含部分黄铁矿的混合泥质砂岩岩样的导电规律。实现了含黄铁矿混合泥质砂岩地层饱和度的准确求取,有效的提高了复杂储层测井解释评价的精度。     

低阻油层通用有效介质电阻率模型

低电阻率油气层的识别与评价一直是测井解释领域亟待解决的难点和热点问题,而砂岩油气层的低电阻率可能是由于富含分散泥质、层状泥质、骨架含导电矿物、微孔隙发育、高矿化度地层水等因素综合引起的,因此,有必要建立一种适用于上述5种成因类型的低阻油层通用电阻率模型．基于低阻油层人造岩样的实验测量结果和有效介质对称各向异性导电理论,针对不同成因低阻油层形成机理,建立了适用5种内因成因类型的低阻油层通用有效介质电阻率模型．通过对该模型的影响因素分析,从理论上说明该模型可以描述5种内因成因弓I起的低阻油层的导电规律,同时,发现泥质分布形式对模型计算的含水饱和度有很大的影响;地层电阻增大系数随层状泥质电导率和含量、分散黏土含量以及骨架颗粒电导率的增大而减小;随骨架渗滤指数和微孔隙水渗滤速率的增大,及微孔隙水渗滤指数、骨架渗滤速率和可动水渗滤速率的减小而减小．通过不同成因低阻岩心实验数据的验证和实际资料解释,表明提出的模型适用于高矿化度地层水、富含分散泥质、微孔隙发育、层状泥质、骨架导电等5种成因的低阻油层解释,是解决低阻油层问题的通用电阻率模型．     

泥质分布形式对泥质砂岩电性的影响规律研究

介绍了将混合理论用于结构泥质、将基于距离的升尺度(DBU)方法用于层状泥质电性研究的原理和方法,通过对实际岩心资料以及井资料的分析处理,证实了将混合理论用于结构泥质、将DBU方法用于层状泥质砂岩电性研究的合理性,最后利用上述方法进一步分析了泥质含量、泥质的分布形式等对泥质砂岩电阻率的影响及规律,研究结果表明:随着泥质含量的增加,泥质砂岩电阻率逐渐降低,且降低的幅度随含水饱和度的降低而增大;当测量电流方向与层状泥质垂直时,泥质对电性的影响较弱,但层状泥质和结构泥质的相对含量对结果的影响很大;当测量电流方向与层状泥质平行时,泥质对电性的影响较强,但层状泥质和结构泥质的相对含量对结果的影响不大.     

含黄铁矿泥质砂岩电阻率频散规律实验研究与校正方法（英文）

含黄铁矿泥质岩石的频散特性使得地层的电阻率测井响应值在高频电阻率测井中会出现失真现象,导致储层的饱和度计算存在较大的难度。为了更好的消除岩石中黄铁矿和泥质的电阻率频散影响,同时弥补天然岩心中各种物质成分、含量,以及分布形式等因素无法人工控制的不足,本文设计并在高温高压下制作了12块含分散状黄铁矿颗粒和粘土颗粒的人造固结岩样,分析岩样在多种电流频率条件下,不同地层水矿化度以及饱和度的岩电实验数据,得出频率对含黄铁矿泥质砂岩导电规律的影响:分散状黄铁矿和粘土颗粒都具有频散特性;随着电流频率的增大,岩样复电阻率实部减小。基于有效介质对称导电理论,结合实验研究成果,考虑黄铁矿含量和泥质含量变化对岩石频散规律的影响,建立了黄铁矿泥质砂岩有效介质复电阻率实部频散模型。理论模拟表明当电流频率、黄铁矿及分散泥质含量变化时,模型预测的黄铁矿泥质砂岩频散规律与实验规律相一致。利用岩电实验数据,验证了该模型可以准确地描述含黄铁矿泥质砂岩储层的频散特征。通过选取多种电测井中应用的电流频率,建立了黄铁矿电导率为0.062 S/m,泥质电导率为0.031 S/m的电阻率频率影响校正图版,给出了运用该图版进行高频电阻率测井响应校正的具体方法,为获取地层的真实电阻率值提供了保障。     

有效介质对称导电理论在复杂泥质砂岩中应用基础研究

复杂泥质砂岩储层的饱和度评价一直是测井解释领域亟待解决的难点和热点问题,基于并联导电理论和阿尔奇公式建立的导电模型扩展性有限,在一定程度上限制了该类模型扩展描述孔隙结构更复杂的高泥高钙砂岩储层的导电规律,而有效介质对称导电理论能很好地描述复杂泥质砂岩储层导电规律,具有很好的应用前景,但仍需深入研究.首先针对纯砂岩,使用有效介质对称导电理论建立纯砂岩有效介质对称导电模型,理论分析与实验研究表明纯砂岩有效介质对称导电模型优于阿尔奇方程,不但可以描述纯砂岩阿尔奇规律,而且可以描述纯砂岩非阿尔奇规律,并且满足当孔隙度等于1时地层因素等于1,以及当含水饱和度等于1时电阻增大系数等于1的物理约束,可更好地描述纯砂岩导电规律.其次,针对分散泥质砂岩,使用有效介质对称导电理论建立泥质砂岩有效介质对称导电模型,理论分析与实验研究表明,泥质砂岩有效介质对称导电模型优于泥质电阻率模型和双电层模型,不需要采用经验拟合就能完整地描述饱含水分散泥质砂岩的电导率与地层水电导率之间曲线和直线关系,模型预测的粘土含量和粘土电导率变化对岩石导电规律的影响与理论认识相符,可更好地描述分散泥质砂岩导电规律.第三,针对两组分混合介质,使用有效介质对称导电理论、并联导电理论、串联导电理论,分别建立了有效介质对称导电方程、并联导电方程、串联导电方程,理论比较表明有效介质对称导电理论与并联导电理论和串联导电理论均不等价,即当两种组分混合介质遵循并联或串联导电规律时,混合介质的导电规律不能用有效介质对称导电理论描述.有效介质对称导电理论能够描述骨架和水以及粘土均为连续项的岩石导电规律.它通过引入渗滤指数和渗滤速率几何参数来描述各种组份的连通性、表面的粗糙度、形状、润湿性等对岩石导电性的影响,因此,有效介质对称导电理论的适用性更广,可用于描述孔隙结构更复杂的高泥高钙砂岩储层的导电规律.     

泥质砂岩中接触胶结泥质定量估算及对砂岩弹性的影响

在泥质砂岩的岩石物理建模中,明确泥质砂岩中泥质胶结物的接触类型及其含量对正确认识泥质的胶结作用对泥质砂岩声速的影响以及合理地建立岩石物理模型至关重要.现阶段,尚未有实验室定量估算胶结泥质的方法,导致应用胶结砂岩理论模型预测胶结砂岩地层的声速时往往由于胶结物含量被高估从而导致预测声速结果偏高.本文通过观察铸体薄片中泥质与颗粒之间的接触关系和相对分布提出了一种区分胶结泥质和分散泥质的方法:与两个或两个以上颗粒接触的连续分布的泥质为胶结泥质;与一个颗粒接触或者不与颗粒接触的泥质为分散泥质.基于这一准则,本文基于像素拾取法估算了人造泥质砂岩的胶结泥质含量,并将胶结泥质含量作为胶结砂岩模型的输入参数优化CCT模型.对比原始模型,本文方法声速误差下降了20%,预测准确度显著提高.本文方法适用于弱胶结地层的岩石物理建模,能够准确的预测声速以结合地震和测井资料识别有利储层,定量评价储层参数.     

泥质含量及其分布形式对岩电关系影响的数字岩心仿真(英文)

由于泥质所造成的附加导电现象,泥质含量及其分布形式对电阻率增大系数I和含水饱和度Sw关系具有重要影响,由于岩石物理实验中岩心孔隙结构及其组分构成、分布的微观不可调性,因而泥质分布形式所造成的影响很难通过岩心实验来单独研究。基于数字岩心的格子气自动机方法是一种有效的微观数值模拟方法,本研究利用储层岩心薄片的骨架颗粒尺寸信息资料建立数字岩心模型,结合格子气自动机技术对数字岩心不同饱和流体情况下电的传输特性进行数值模拟研究,揭示了不同泥质含量和泥质分布形式对孔隙介质导电特性非阿尔奇现象产生的影响,建立饱和度指数和泥质含量之间的关系模型,其良好的吻合性表明该方法在岩石物理研究中是一种十分有效的研究方法,而新模型适于在非阿尔奇储层进行准确的饱和度评价。     

新疆塔北低阻油气储层导电模型--双水泥质骨架导电模型

对前人提出的泥质分布型、双水型、岩石骨架等导电模型的剖析,发现有的模型没有区分微孔隙水与地层水的性质和导电路径;有的模型没有区分微孔隙水和粘土水的导电路径;有的模型没有考虑泥质分布形式和泥质数量等.为此,吸取了这些模型的优点,克服其不足,结合新疆塔北地区泥质砂岩低阻油气储层的特征及成因,建立了一个新的泥质砂岩导电模型--双水泥质骨架导电模型(Dual-Water Clay Matrix Conductive Model,缩写为DWCMCM),双水是自由水和微孔隙水,泥质骨架是含有粘土水的粘土颗粒.DWCMCM区分不同水的性质和导电路径,并考虑了泥质分布形式和泥质数量,因此DWCMCM评价新疆塔北地区泥质砂岩低阻油气储层的结果与实际储层情况相符.     

低孔渗泥质砂岩储层并联导电模型分析及改进

针对泥质砂岩储层最常用的并联导电模型W-S和双水模型,提出视地层因数与真实地层因数的比值F_a/F,用来表示泥质砂岩偏离阿尔奇砂岩的程度,并根据F_a/F的变化规律,分析Q_v对泥质砂岩储层导电模型的影响.结合实验室条件下Nacl溶液的电导率范围,指出W-S模型在泥质较重的地层中无法得到真实的地层因数.改进双水模型的计算方法,避开Q_v测量的不准确性带来的误差,而通过改变饱和溶液的电导率来得到岩样真实的地层因数.实验证明,改进双水模型的模拟结果比W-S模型与泥质砂岩的岩电实验数据更吻合.     

Conductivity model for pyrite-bearing laminated and dispersed shaly sands based on a differential equation and the generalized Archie equation

The conductance of pyrite-bearing laminated and dispersed shaly sands is not well understood and resistivity models for pyrite-bearing shaly sands are nonexistent. Thus, we first synthesize clean pyrite-matrix samples, and quartz-matrix samples with variable laminated shale, dispersed shale, and pyrite content and then perform petrophysics experiments to assess the effect of pyrite content on the conductivity of pyrite-bearing shaly sands. Second, based on the differences in conductivity and conduction pathways and geometries because of the variable composition of the pyrite-bearing laminated and dispersed shaly sands, we divide the shaly sands into their components, i.e., laminated shale, quartz grains, pyrite grains, hydrocarbon, dispersed shale, microscopic capillary water, and mobile water. A generalized resistivity model is proposed to describe the conductivity of pyrite-bearing laminated and dispersed shaly sands, based on the combined conductivity differential equation and generalized Archie equation. In the generalized resistivity model, the conductivity differential equation is used to describe the conductivity of dispersed inclusions in a host, whereas the generalized Archie equation is used to describe the conductivity of two conducting phases. Moreover, parallel conductance theory is used to describe the conductivity of dispersed shaly sands and laminated shale. Theoretical analysis suggests that the proposed model satisfies the physical constraints and the model and experimental results agree. The resistivity and resistivity index of shaly sands decrease with increasing conductivity and pyrite. Finally, the accuracy of the resistivity model is assessed based on experimental data from 46 synthetic core samples with different oil saturation. The model can describe the conductivity of clean pyrite-matrix samples, and quartz-matrix samples with different volumes of laminated shale, dispersed shale, and pyrite. An accurate saturation model of pyrite-bearing laminated and dispersed shaly sands is thus obtained and the log data interpretation in complex shaly sands can improve with the proposed model.     

Generalized effective medium resistivity model for low resistivity reservoir

With the advancement in oil exploration,producible oil and gas are being found in low resistivity reservoirs,which may otherwise be erroneously thought as water zones from their resistivity.However,the evaluation of low resistivity reservoirs remains difficult from log interpretation.Since low resistivity in hydrocarbon bearing sands can be caused by dispersed clay,laminated shale,conductive matrix grains,microscopic capillary pores and high saline water,a new resistivity model is required for more accurate hydrocarbon saturation prediction for low resistivity formations.Herein,a generalized effective medium resistivity model has been proposed for low resistivity reservoirs,based on experimental measurements on artificial low resistivity shaly sand samples,symmetrical anisotropic effective medium theory for resistivity interpretations,and geneses and conductance mechanisms of low resistivity reservoirs.By analyzing effects of some factors on the proposed model,we show theoretically the model can describe conductance mechanisms of low resistivity reservoirs with five geneses.Also,shale distribution largely affects water saturation predicted by the model.Resistivity index decreases as fraction and conductivity of laminated shale,or fraction of dispersed clay,or conductivity of rock matrix grains increases.Resistivity index decreases as matrix percolation exponent,or percolation rate of capillary bound water increases,and as percolation exponent of capillary bound water,or matrix percolation rate,or free water percolation rate decreases.Rock sample data from low resistivity reservoirs with different geneses and interpretation results for log data show that the proposed model can be applied in low resistivity reservoirs containing high salinity water,dispersed clay,microscopic capillary pores,laminated shale and conductive matrix grains,and thus is considered as a generalized resistivity model for low resistivity reservoir evaluation.     

Low resistivity oil(gas)-bearing reservoir conductive model --Dual water clay matrix conductive model in the north area of Tarim Basin, Xinjiang, China

Shaly sands reservoir is one of the most distributive types of the oil(gas)-bearing reservoirs discovered in China, and low resistivity oil(gas)-bearing reservoirs are mostly shaly sands reservoirs. Therefore, shaly sands reservoir conductive model is the key to evaluate low resistivity oil(gas)-bearing reservoirs using logging information. Some defects were found when we studied the clay distribution type conductive model, dual-water conductive model, conductive rock matrix model, etc. Some models could not distinguish the conductive path and nature of microporosity water and clay water and some models did not consider the clay distribution type and the mount of clay volume. So, we utilize the merits,overcome the defects of the above models, and put forward a new shaly sands conductive model-dual water clay matrix conductive model (DWCMCM) in which dual water is the free water and the microporosity water in shaly sands and the clay matrix(wet clay) is the clay grain containing water. DWCMCM is presented here, the advantages of which can tell the nature and conductive path from different water (microporosity water and freewater), in consid-eration of the clay distribution type and the mount of clay volume in shaly sands. So, the results of logging interpretation in the oil(gas)-bearing reservoirs in the north of Tarim Basin area, China with DWCMCM are better than those interpreted by the above models.     

Low resistivity oil(gas)-bearing reservoir conductive model Dual water clay matrix conductive model in the north area of Tarim Basin, Xinjiang, China

Shaly sands reservoir is one of the most distributive types of the oil(gas)-bearing reservoirs discovered in China, and low resistivity oil(gas)-bearing reservoirs are mostly shaly sands reservoirs. Therefore, shaly sands reservoir conductive model is the key to evaluate low resistivity oil(gas)-bearing reservoirs using logging information. Some defects were found when we studied the clay distribution type conductive model, dual-water conductive model, conductive rock matrix model, etc. Some models could not distinguish the conductive path and nature of microporosity water and clay water and some models did not consider the clay distribution type and the mount of clay volume. So, we utilize the merits,overcome the defects of the above models, and put forward a new shaly sands conductive model—dual water clay matrix conductive model (DWCMCM) in which dual water is the free water and the microporosity water in shaly sands and the clay matrix(wet clay) is the clay grain containing water. DWCMCM is presented here, the advantages of which can tell the nature and conductive path from different water (microporosity water and free-water), in consideration of the clay distribution type and the mount of clay volume in shaly sands. So, the results of logging interpretation in the oil(gas)-bearing reservoirs in the north of Tarim Basin area, China with DWCMCM are better than those interpreted by the above models.     

Rock physics model for seismic velocity & fluid substitution in sub-resolution interbedded sand–shale sequences

The measured geophysical response of sand – shale sequences is an average over multiple layers when the tool resolution (seismic or well log) is coarser than the scale of sand – shale mixing. Shale can be found within sand – shale sequences as laminations, dispersed in sand pores, as well as load bearing clasts. We present a rock physics framework to model seismic/sonic properties of sub-resolution interbedded shaly sands using the so-called solid and mineral substitution models. This modelling approach stays consistent with the conceptual model of the Thomas–Stieber approach for estimating volumetric properties of shaly sands; thus, this work connects established well log data-based petrophysical workflows with quantitative interpretation of seismic data for modelling hydrocarbon signature in sand – shale sequences. We present applications of the new model to infer thickness of sand – shale lamination (i.e., net to gross) and other volumetric properties using seismic data. Another application of the new approach is fluid substitution in sub-resolution interbedded sand–shale sequences that operate directly at the measurement scale without the need to downscale; such a procedure has many practical advantages over the approach of “first-downscale-and-then-upscale” as it is not very sensitive to errors in estimated sand fraction and end member sand/shale properties and remains stable at small sand/shale fractions.     

Effect of Shale Distribution on Hydrocarbon Sands Integrated with Anisotropic Rock Physics for AVA Modelling: A Case Study

Shales can be distributed in sand through four different ways; laminated, structural, dispersed and any combination of these aforementioned styles. A careful analysis of well log data is required for the determination of shale distribution in sand affecting its reservoir quality. The objective of this study is to characterize the effect of shale distribution on reservoir quality of sands using well log data. The correlation of well data in terms of lithology has revealed four sand and three shale layers in Lower Goru Formation acting as a major reservoir in the study area. Our results indicate that the laminated type of shale distribution prevails at the Basal sand level, which does not affect its reservoir quality greatly. The remaining layers of variable vertical extent show a variety of shale distribution models affecting their reservoir quality adversely. We also present anisotropic rock physics modelling for AVA analysis at Basal sand level.     

A physical model for shear-wave velocity prediction1

The clay-sand mixture model of Xu and White is shown to simulate observed relationships between S-wave velocity (or transit time), porosity and clay content. In general, neither S-wave velocity nor S-wave transit time is a linear function of porosity and clay content. For practical purposes, clay content is approximated by shale volume in well-log applications. In principle, the model can predict S-wave velocity from lithology and any pair of P-wave velocity, porosity and shale volume. Although the predictions should be the same if all measurements are error free, comparison of predictions with laboratory and logging measurements show that predictions using P-wave velocity are the most reliable. The robust relationship between S- and P-wave velocities is due to the fact that both are similarly affected by porosity, clay content and lithology. Moreover, errors in the measured P-wave velocity are normally smaller than those in porosity and shale volume, both of which are subject to errors introduced by imperfect models and imperfect parameters when estimated from logs. Because the model evaluates the bulk and shear moduli of the dry rock frame by a combination of Kuster and Toksöz’ theory and differential effective medium theory, using pore aspect ratios to characterize the compliances of the sand and clay components, the relationship between P- and S-wave velocities is explicit and consistent. Consequently the model sidesteps problems and assumptions that arise from the lack of knowledge of these moduli when applying Gassmann's theory to this relationship, making it a very flexible tool for investigating how the v_P-v_s relationship is affected by lithology, porosity, clay content and water saturation. Numerical results from the model are confirmed by laboratory and logging data and demonstrate, for example, how the presence of gas has a more pronounced effect on P-wave velocity in shaly sands than in less compliant cleaner sandstones.     

三电阻率覆盖法直观识别油、水层

本文论述三电阻率覆盖法,采用测量的地层电阻率与计算的水层电阻率和油层临界电阻率覆盖,提高了直观识别砂-泥岩剖面油、水层的准确性。 油田应用实例指出,三电阻率覆盖法能够有效地直观识别砂岩和泥质砂岩油、水层,计算油层有效含水饱和度,同时还能够有效地直观识别钙质砂岩地层。