前梨园地区深层致密气超压特征及成藏效应

以致密气藏为代表的非常规油气藏勘探在国内逐渐得到重视.前梨园洼陷是东濮凹陷最大的生油气洼陷,展示了极好的深层超压天然气勘探前景.在实测压力基础上,结合声波时差及地震速度计算,利用东濮凹陷丰富的测井、测试和地质资料综合分析超压分布和成因.结果表明:前梨园地区地层压力在纵向上具有典型双层结构,其中沙三中下亚段超压普遍发育.泥岩层的压力分布与砂岩储层的压力分布特征具有一定差异,泥岩欠压实所产生的增压并不显著,生烃作用尤其是大量生气为区域超压形成的主要机制.超压的存在对天然气运聚成藏产生重要的影响.超压通过对成岩作用的影响,改善了深部砂岩储层物性从而提高储集性能.相同深度和储集条件下,油气层压力越高,相应含油气饱和度增高.加强超压相关研究对于本区深层致密砂岩气藏勘探意义重大.     

油水饱和泥质砂岩流动电位的频散特性

油水饱和泥质砂岩中流动电位的研究对于揭示含油储层震电勘探和动电测井的机理有着重要的意义.本文首先从岩石孔隙的微观结构出发,构造了描述水润湿条件下油水饱和泥质砂岩储层的毛管模型.在模型中依据油水流动遵守的Navier-Stokes方程和电化学传质动力学理论,建立了描述油水饱和泥质砂岩流动电位的数学方程,并数学模拟了岩石储渗参数对流动电位频散特性的影响规律.研究结果表明:储层孔隙内流体受到的粘滞力与惯性力控制着水相和油相的流动,从而决定了流动电位的频散特性.随着孔隙度的增大,油水两相各自的有效渗透率均增大;而含水饱和度的升高使得水相有效渗透率增大,油相有效渗透率减小.在水润湿条件下,流动电位耦合系数随含水饱和度升高而增大,随束缚水饱和度的升高而减小.另外,流动电位相对耦合系数也随含水饱和度的升高而增大,但无频散现象.     

利用毛管模型研究泥质砂岩电化学测井响应机理

自然电位和激发极化电位测井响应所涉及的离子导体激发极化电位的微观机理解释,主要依据双电层形变假说和浓差极化假说,缺少定量描述的数学模型和理论体系.本文利用孔隙介质的微观毛管模型,给出了毛管模型中双电层理论和阳离子交换量与Zeta电位的关系,推导出毛管中离子流量和电流强度表达式.由电荷守恒定律和物质守恒定律,推导出毛管中离子浓度分布的解析表达式,建立了描述含水泥质砂岩激发极化电位和自然电位的数学模型.从而系统地严格证明了含水泥质砂岩激发极化现象是在电流场和浓度梯度场的共同作用下,由孔隙中离子浓度浓差极化电位和双电层形变电位形成的.并且证明了描述泥质砂岩自然电位的数学方程和描述激发极化电位的数学方程及形成机理是一致的.计算结果表明：激发极化极化率随孔隙度和渗透率的增大而减小;极化率随溶液浓度的增加而减小,随阳离子交换量的增加而增加;证明了地层水浓度、阳离子交换量是影响自然电位大小的主要因素.     

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.     

定量表征压实和胶结作用的砂岩声波速度岩石物理模型

成岩作用是影响砂岩声波速度的地质因素之一,定量表征压实和胶结作用的砂岩声波速度岩石物理模型具有重要的理论和实践应用意义.选取视压实率和视胶结率定量表征砂岩成岩作用,通过建立视压实率与颗粒配位数的关系将压实作用的影响引入修正的定量表征胶结作用的CCT模型,最终建立了一种能够定量表征压实和胶结作用对砂岩声波速度影响的岩石物理模型.理论考察发现,随胶结率的增大,岩石声波速度首先迅速增大,随后趋于稳定;随视压实率增大,岩石声波速度同样逐渐增大,当胶结率较大时声波速度变化更为明显.为了验证该声波速度模型,分别对人造砂岩和天然样品进行了声波速度实验观测,结果表明：实验结果与理论分析的趋势吻合良好.该模型易于使用,能够为应用地震和测井资料识别有利储层、定量评价孔隙度以及开展横波速度预测等应用提供理论基础.     

川中古隆起超压分布与形成的地温场因素

温度和压力是沉积盆地两个重要的物理场,温度影响着超压的形成和分布.本文根据钻孔实测温度和压力数据分析了川中古隆起现今压力与温度的关系;在实验室对封闭流体进行了多组温-压关系实验;利用等效镜质体反射率和包裹体测温数据恢复了川中古隆起不同井区在白垩纪抬升之前的最大古地温,并在此基础上分析了温度降低对研究区超压的影响;最后探讨了生烃增压和欠压实超压形成过程中温度的作用.研究结果表明,川中古隆起现今超压层的压力系数与温度呈正相关关系;在绝对密封的条件下,当压力大于15 MPa时,温度每变化1℃,压力变化1.076 MPa.川中地区不同井区自晚白垩世以来的差异性降温是现今同一超压层系超压强度不同的主要因素,此外超压层还应发生了流体的横向压力传递和泄漏.下古生界原油裂解形成超压的时间是180~110 Ma;气态烃伴生的盐水包裹体均一温度暗示了在90 Ma超压发生调整.盆地模拟结果显示温度对上三叠统须家河组的欠压实增压影响微弱.     

超浅疏松地层泥质粉砂岩与粉砂质泥岩识别方法——以大庆某地区黑帝庙层为例

超浅疏松地层压实程度低,未压实的粉砂质泥岩具有一定的孔隙度,与泥质粉砂岩的电性特征相接近,不易区分.本文针对这一难题,提出了稳定泥质单元控制下的岩性划分技术.该技术的核心思想是:在测井曲线上将厚层稳定的泥岩段定义为泥质单元,将泥质单元所分隔的大套砂体部分定义为非泥质单元.在泥质单元内采用电阻率的回返率和自然伽马的交会识别泥质粉砂岩和粉砂质泥岩;在非泥质单元内,按照沉积韵律控制下电阻率曲线的相对变化来区分泥质粉砂岩和粉砂质泥岩.而针对不包含在任何韵律内的2种岩性,采用3参数、4种电测曲线交会分区识别.以密闭取心井岩性分析结果为标准,采用该套技术共解释岩性58层,误判4层,岩性判别总符合率达到93.1%.其中,判别泥质粉砂岩和粉砂质泥岩32层,符合率达到87.5%.     

鄂尔多斯盆地三叠系延长组相对高放射性砂岩定量识别（英文）

相对高放射性砂岩储层多数具可观的油气资源潜力。相对高放射性砂岩因其具有与泥质地层相类似的放射性测井响应特征而常被误判进而会导致有效储层遗漏。本文在分析常规砂、泥岩地层中自然电位曲线与自然伽马曲线响应特征及关系的基础上,提出了相对高放射性砂岩定量识别方法。以鄂尔多斯盆地三叠系延长组为例:常规砂、泥岩地层中的自然电位曲线与自然伽马曲线响应具有同步性且呈正相关,然而在相对高放射性砂岩中两者并不同步。基于这一关系,实现了相对高放射性砂岩定量化识别,并对自然伽马曲线进行了放射性"虚拟补偿",同时就其测井评价方法进行了探讨。实例表明本文提出的方法有效,可以减少对储层的误判和遗漏。     

层状孔隙介质孔隙度对地震属性影响分析

孔隙度是储层的重要参数之一,学者提出了多种根据地震属性分析孔隙度大小的方法.然而,层状孔隙介质中孔隙度对地震属性的影响至今没有系统的论述.鉴于此,本文建立了两种类型储层:其一为深度压实,固结程度好的储层;其二为欠压实,固结程度差的储层.对于上述两种类型储层,通过理论和数值模拟,分析了孔隙度对地震属性(与频率相关)的影响.研究表明,对于深度压实储层,反射系数随孔隙度的增加而减小;对于欠压实储层,反射系数随孔隙度的增加而增加.     

砂泥岩储层岩石物理交会模板构建

岩石物理是研究储层参数和岩石弹性参数之间关系的基础,在储层特性和地震特性之间起到了桥梁作用.为了更加精细的识别岩性,更好的进行砂泥岩储层油气的识别和预测,需要基于岩石物理寻找有效的识别方法.本文基于微分等效介质理论构建了砂泥岩储层岩石物理模型.为了考虑砂泥岩储层流体分布的非均匀性,模型中采用了斑块状饱和理论.文中分析了砂泥岩弹性参数和储层物性之间的关系,给出了各物性参数对弹性参数的影响结果,并根据储层物性的影响绘制了弹性参数交会模板.不同于常规交会分析,该弹性参数交会模板综合考虑了孔隙度、含水饱和度、泥质含量和孔隙纵横比等参数的影响,更加真实地反应了储层的地下特征.该交会模板的优势在于可以合理的界定出储层的砂、泥岩范围,而且根据泥质含量等参数的不同,可以进一步界定储层岩性的范围,为储层岩性的精细识别提供了新的方法.通过实际井资料的应用,该交会模板做到了砂泥岩储层岩性的有效区分,另外根据交会模板中泥质含量的不同,由0.5到0.25,我们可以在地震剖面中做出砂岩储层范围的精细界定,较好地识别了岩性,为寻找储层提供可靠依据.     

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.     

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.     

Constraints on velocity-depth trends from rock physics models

Estimates of depth, overpressure and amount of exhumation based on sonic data for a sedimentary formation rely on identification of a normal velocity–depth trend for the formation. Such trends describe how sonic velocity increases with depth in relatively homogeneous, brine‐saturated sedimentary formations as porosity is reduced during normal compaction (mechanical and chemical). Compaction is ‘normal’ when the fluid pressure is hydrostatic and the thickness of the overburden has not been reduced by exhumation. We suggest that normal porosity at the surface for a given lithology should be constrained by its critical porosity, i.e. the porosity limit above which a particular sediment exists only as a suspension. Consequently, normal velocity at the surface of unconsolidated sediments saturated with brine approaches the velocity of the sediment in suspension. Furthermore, porosity must approach zero at infinite depth, so the velocity approaches the matrix velocity of the rock and the velocity–depth gradient approaches zero. For sediments with initially good grain contact (when porosity is just below the critical porosity), the velocity gradient decreases with depth. By contrast, initially compliant sediments may have a maximum velocity gradient at some depth if we assume that porosity decreases exponentially with depth. We have used published velocity–porosity–depth relationships to formulate normal velocity–depth trends for consolidated sandstone with varying clay content and for marine shale dominated by smectite/illite. The first relationship is based on a modified Voigt trend (porosity scaled by critical porosity) and the second is based on a modified time‐average equation. Baselines for sandstone and shale in the North Sea agree with the established constraints and the shale trend can be applied to predict overpressure. A normal velocity–depth trend for a formation cannot be expressed from an arbitrary choice of mathematical functions and regression parameters, but should be considered as a physical model linked to the velocity–porosity transforms developed in rock physics.     

不同泥质分布形式泥质砂岩导电规律实验研究

本文利用人工制作的不同含量分散泥质和层状泥质砂岩岩心样品,测量不同矿化度和不同含油饱和度的岩心电阻率,从实验角度研究了不同泥质分布形式和含量的岩心导电规律,结果表明,泥质分布形式或含量不同,则泥质砂岩导电规律不同.基于层状泥质与分散泥质砂岩的并联导电实验规律,以及分散粘土和地层水混合物的导电规律可用HB电阻率方程描述,建立了考虑泥质分布形式影响的泥质砂岩电阻率模型.通过1组不同泥质分布形式泥质砂岩人造岩心实验数据的测试,表明该模型可以描述分散泥质砂岩、层状泥质砂岩和混合泥质砂岩地层的导电规律.分散泥质,层状泥质,人造岩样,实验测量,并联导电,HB方程,电阻率模型     

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.     

Compaction trend versus seismic anisotropy in shaly formations

Shales comprise more than 60% of sedimentary rocks and form natural seals above hydrocarbon reservoirs. Their sealing capacity is also used for storage of nuclear wastes. The world's most important conventional oil and gas reservoirs have their corresponding source rocks in shale. Furthermore, shale oil and shale gas are the most rapidly expanding trends in unconventional oil and gas. Shales are notorious for their strong elastic anisotropy, i.e., so‐called vertical transverse isotropy. This vertical transverse isotropy, characterised by a vertical axis of invariance, is of practical importance as it is required for correct surface seismic data interpretation, seismic to well tie, and amplitude versus offset analysis. A rather classical paradigm makes a clear link between compaction in shales and the alignment of the clay platelets (main constituent of shales). This would imply increasing anisotropy strength with increasing compaction. Our main purpose is to check this prediction on two large databases in shaly formations (more than 800 samples from depths of 0–6 km) by extracting the major trends in the relation between seismic anisotropy and compaction. The statistical analysis of the database shows that the simultaneous increase in density and velocity, a classical compaction signature, is quite weakly correlated with the anisotropy strength. As a consequence, compaction can be excluded as a major cause of seismic anisotropy, at least in shaly formations. Also, the alignment of the clay platelets can explain most of the anisotropy measurements of both databases. Finally, a method for estimating the orientation distribution function of the clay platelets from the measurement of the anisotropy parameters is suggested.     

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.