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ZHAO Jing, HUANG ZhiLong, ZHANG JingYuan, DENG GuangJun, XU MaGuang. Pore Structure Fractal and Graded Evaluation in Tight Sandstone Reservoirs: A case study of the Huangliu Formation in the Ledong area, Yinggehai Basin[J]. Acta Sedimentologica Sinica, 2024, 42(1): 295-308. doi: 10.14027/j.issn.1000-0550.2022.038
Citation: ZHAO Jing, HUANG ZhiLong, ZHANG JingYuan, DENG GuangJun, XU MaGuang. Pore Structure Fractal and Graded Evaluation in Tight Sandstone Reservoirs: A case study of the Huangliu Formation in the Ledong area, Yinggehai Basin[J]. Acta Sedimentologica Sinica, 2024, 42(1): 295-308. doi: 10.14027/j.issn.1000-0550.2022.038

Pore Structure Fractal and Graded Evaluation in Tight Sandstone Reservoirs: A case study of the Huangliu Formation in the Ledong area, Yinggehai Basin

doi: 10.14027/j.issn.1000-0550.2022.038
Funds:

Sub Subject of the Key Technology Pro-ject of CNOOC, No. CNOOC-KJ 135 ZDXM 38 ZJ 02 ZJ CNOOC-KJ 135 ZDXM 38 ZJ 02 ZJ

  • Received Date: 2021-11-03
  • Accepted Date: 2022-04-24
  • Rev Recd Date: 2022-04-01
  • Available Online: 2022-04-24
  • Publish Date: 2024-02-10
  • Objective Tight sandstone reservoirs have small pore throats,various pore throat types,and strong heterogeneity. Clarifying the micro morphology of pore throat in tight sandstone reservoirs and dividing the grading of reservoir pore structure are important for evaluating the reservoir quality. Multi angle and semi quantitative evaluation of reservoir capacity and flow characteristics is helpful for clarifying the types of reservoirs with high productivity potential. Methods Taking the tight sandstones of the Huangliu Formation in the Ledong area of Yinggehai Basin as an example,this study uses the experimental methods of casting thin section,scanning electron microscope (SEM),and high-pressure mercury injection (HPMI). By analyzing the reservoir diagenesis,dividing the reservoir pore throat types,and calculating fractal dimension parameters,the pore structure characteristics are clarified. To analyze the influence of reservoir microstructure parameters on macro physical properties,the pore throat radius scale and the tight sandstone reservoir types are divided,and research on fractal dimension calculation and grading evaluation of reservoir pore structure is performed. Results The HPMI experimental results show that the pore-throat radius of tight sandstone reservoirs in the Huangliu Formation has a bimodal distribution,the displacement pressure is between 0.14-2.75 MPa,and the average pore throat radius is between 0.08-1.10 μm. For a better reservoir type,the proportion of the large pore-throat is higher. Using the HPMI fractal dimension (D) to evaluate the pore-throat structure characteristics of the Huangliu Formation reservoirs,when the fractal dimension is closer to 3,the pore throat radius is smaller,the throat is more complex,and the reservoir quality worsens. Owing to the double peak distribution of the pore-throat radius in the Huangliu Formation tight reservoirs,the mercury inlet curves display segmentation. Therefore,the fractal dimensions of large pore throat (Dmax) and small pore throat (Dmin) are calculated in this study. The Dmax value has the strongest correlation with porosity and permeability. The pore structure characteristics of large pore-throat are one of the important factors affecting the reservoir quality. Based on the intersection of the two linear fitting curves in the lgSHg-lgPc diagram and whether mercury is injected into the pore space,the tight sandstone is divided into three levels: large,small,and isolated pore-throats. The closer the fractal dimension is to 2,the more connected the large pore-throat spaces are in the reservoirs,and the correlation between large pore-throat porosity and permeability is higher. Therefore,the large pore-throat can more effectively characterize the reservoir quality and pore throat structure. Based on the grading characteristics of pore throats,diagenetic facies,and the complexity of pore structure,four types of models for grading evaluation of pore structure are established. Type Ⅰ is the small pore-throat dominant reservoirs with strongly cemented diagenetic facies,and the proportion of large pore-throat porosity is less than 45%. The D value ranges from 2.70-2.80,and the Dmax value is 2.75-2.90,with an isolated point-single point connecting bundle throat and tight reservoir. Type Ⅱ is the large to small pore-throat continuous reservoirs,with weakly cemented and dissolved diagenetic facies. Large pore-throat porosity accounts for 45%-70%. The D value is 2.60-2.80,and the Dmax value is 2.70-2.85,in a single-point and multi-point connecting curved sheet throat,low permeability reservoir. Type Ⅲ is the large pore-throat dominant reservoirs,with strong dissolution diagenetic facies. Large pore-throat porosity accounts for more than 70%. The D value distribution is 2.55-2.60,and the Dmax value is 2.55-2.65,in a network connection thick throat,high-quality reservoir. Type Ⅳ is the single peak reservoir with large pore-throat and strongly compacted diagenetic facies. Large pore-throat porosity accounts for 50%-60%. The D value distribution is 2.70-2.80,and the Dmax value is 2.65-2.75,in a multi-point connection of tube bundle throat,low permeability reservoir. Using the reservoir permeability,porosity,and Dmax parameters,through Fisher's discriminant method,new parameters F1 and F2 are obtained,and the reservoir type discrimination criteria were established. Finally,the logging prediction model of reservoir type is established. Comparing the reservoir type with gas logging response and gas saturation,under the same geological background,the gas logging response in type Ⅲ,type Ⅱ,and type Ⅰ reservoirs is shown to gradually decrease. Type Ⅲ reservoir has strong reservoir and seepage capacity,high gas production efficiency,and good exploration value. Type Ⅳ reservoirs can be used as a barrier in sand bodies,and type Ⅰ reservoirs have poor reservoir capacity. Conclusion Using reservoir diagenesis,pore structure characteristics,and fractal dimension parameters,the tight sandstone reservoir quality can be semi-quantitatively classified,providing a new idea for tight sandstone reservoir evaluation and classification,and clarifying the control effect of reservoir pore structure on gas-water distribution.
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  • Received:  2021-11-03
  • Revised:  2022-04-01
  • Accepted:  2022-04-24
  • Published:  2024-02-10

Pore Structure Fractal and Graded Evaluation in Tight Sandstone Reservoirs: A case study of the Huangliu Formation in the Ledong area, Yinggehai Basin

doi: 10.14027/j.issn.1000-0550.2022.038
Funds:

Sub Subject of the Key Technology Pro-ject of CNOOC, No. CNOOC-KJ 135 ZDXM 38 ZJ 02 ZJ CNOOC-KJ 135 ZDXM 38 ZJ 02 ZJ

Abstract: Objective Tight sandstone reservoirs have small pore throats,various pore throat types,and strong heterogeneity. Clarifying the micro morphology of pore throat in tight sandstone reservoirs and dividing the grading of reservoir pore structure are important for evaluating the reservoir quality. Multi angle and semi quantitative evaluation of reservoir capacity and flow characteristics is helpful for clarifying the types of reservoirs with high productivity potential. Methods Taking the tight sandstones of the Huangliu Formation in the Ledong area of Yinggehai Basin as an example,this study uses the experimental methods of casting thin section,scanning electron microscope (SEM),and high-pressure mercury injection (HPMI). By analyzing the reservoir diagenesis,dividing the reservoir pore throat types,and calculating fractal dimension parameters,the pore structure characteristics are clarified. To analyze the influence of reservoir microstructure parameters on macro physical properties,the pore throat radius scale and the tight sandstone reservoir types are divided,and research on fractal dimension calculation and grading evaluation of reservoir pore structure is performed. Results The HPMI experimental results show that the pore-throat radius of tight sandstone reservoirs in the Huangliu Formation has a bimodal distribution,the displacement pressure is between 0.14-2.75 MPa,and the average pore throat radius is between 0.08-1.10 μm. For a better reservoir type,the proportion of the large pore-throat is higher. Using the HPMI fractal dimension (D) to evaluate the pore-throat structure characteristics of the Huangliu Formation reservoirs,when the fractal dimension is closer to 3,the pore throat radius is smaller,the throat is more complex,and the reservoir quality worsens. Owing to the double peak distribution of the pore-throat radius in the Huangliu Formation tight reservoirs,the mercury inlet curves display segmentation. Therefore,the fractal dimensions of large pore throat (Dmax) and small pore throat (Dmin) are calculated in this study. The Dmax value has the strongest correlation with porosity and permeability. The pore structure characteristics of large pore-throat are one of the important factors affecting the reservoir quality. Based on the intersection of the two linear fitting curves in the lgSHg-lgPc diagram and whether mercury is injected into the pore space,the tight sandstone is divided into three levels: large,small,and isolated pore-throats. The closer the fractal dimension is to 2,the more connected the large pore-throat spaces are in the reservoirs,and the correlation between large pore-throat porosity and permeability is higher. Therefore,the large pore-throat can more effectively characterize the reservoir quality and pore throat structure. Based on the grading characteristics of pore throats,diagenetic facies,and the complexity of pore structure,four types of models for grading evaluation of pore structure are established. Type Ⅰ is the small pore-throat dominant reservoirs with strongly cemented diagenetic facies,and the proportion of large pore-throat porosity is less than 45%. The D value ranges from 2.70-2.80,and the Dmax value is 2.75-2.90,with an isolated point-single point connecting bundle throat and tight reservoir. Type Ⅱ is the large to small pore-throat continuous reservoirs,with weakly cemented and dissolved diagenetic facies. Large pore-throat porosity accounts for 45%-70%. The D value is 2.60-2.80,and the Dmax value is 2.70-2.85,in a single-point and multi-point connecting curved sheet throat,low permeability reservoir. Type Ⅲ is the large pore-throat dominant reservoirs,with strong dissolution diagenetic facies. Large pore-throat porosity accounts for more than 70%. The D value distribution is 2.55-2.60,and the Dmax value is 2.55-2.65,in a network connection thick throat,high-quality reservoir. Type Ⅳ is the single peak reservoir with large pore-throat and strongly compacted diagenetic facies. Large pore-throat porosity accounts for 50%-60%. The D value distribution is 2.70-2.80,and the Dmax value is 2.65-2.75,in a multi-point connection of tube bundle throat,low permeability reservoir. Using the reservoir permeability,porosity,and Dmax parameters,through Fisher's discriminant method,new parameters F1 and F2 are obtained,and the reservoir type discrimination criteria were established. Finally,the logging prediction model of reservoir type is established. Comparing the reservoir type with gas logging response and gas saturation,under the same geological background,the gas logging response in type Ⅲ,type Ⅱ,and type Ⅰ reservoirs is shown to gradually decrease. Type Ⅲ reservoir has strong reservoir and seepage capacity,high gas production efficiency,and good exploration value. Type Ⅳ reservoirs can be used as a barrier in sand bodies,and type Ⅰ reservoirs have poor reservoir capacity. Conclusion Using reservoir diagenesis,pore structure characteristics,and fractal dimension parameters,the tight sandstone reservoir quality can be semi-quantitatively classified,providing a new idea for tight sandstone reservoir evaluation and classification,and clarifying the control effect of reservoir pore structure on gas-water distribution.

ZHAO Jing, HUANG ZhiLong, ZHANG JingYuan, DENG GuangJun, XU MaGuang. Pore Structure Fractal and Graded Evaluation in Tight Sandstone Reservoirs: A case study of the Huangliu Formation in the Ledong area, Yinggehai Basin[J]. Acta Sedimentologica Sinica, 2024, 42(1): 295-308. doi: 10.14027/j.issn.1000-0550.2022.038
Citation: ZHAO Jing, HUANG ZhiLong, ZHANG JingYuan, DENG GuangJun, XU MaGuang. Pore Structure Fractal and Graded Evaluation in Tight Sandstone Reservoirs: A case study of the Huangliu Formation in the Ledong area, Yinggehai Basin[J]. Acta Sedimentologica Sinica, 2024, 42(1): 295-308. doi: 10.14027/j.issn.1000-0550.2022.038
  • 随着全球对天然气需求的日益增长,非常规天然气的勘探开发已成为全球热点,致密砂岩气藏占据重要的位置[14]。由于非常规致密储层孔隙结构复杂多样,储层非均质性较强,利用孔隙度、渗透率数据难以满足储层评价的需求[47]。致密砂岩储层具有低孔低渗的物性特征,通过孔隙结构参数评价储层质量,可明确储层内部孔喉组成对物性参数的影响[810],辅助储层形成机理、油气水分布的研究。如今,除孔渗、铸体薄片、扫描电镜等实验手段,常利用高压压汞、核磁共振(NMR)、CT扫描等进行储层定量评价[4,7,1112]。利用高压压汞或核磁共振实验结果,进行分形维数计算,能够定量表征孔隙结构复杂程度[1,1314]。分形维数与孔喉结构参数具有良好相关性[14],可划分储层孔喉系统级次[1,13]、预测渗透率[1517]、评价储层渗流性能等[1],是定量评价致密砂岩储层的一种重要手段。

    莺歌海盆地乐东区黄流组致密砂岩储层经历多期成岩作用[18]。黄流组致密砂岩储层非均质性较强,相同孔隙度岩石的渗透率差别较大,利用孔隙度和渗透率划分的储层类型往往与储层生产特征矛盾,而黄流组气藏的含气饱和度低,相邻储层含气量差异较大[19],这与储层的孔隙结构特征密不可分。因此,从致密砂岩储层孔隙结构特征和微观发育模式出发,划分储层类型,对于评价储层生产能力具有重要意义。

  • 莺歌海盆地是中国南部海域内一典型大型走滑—伸展盆地,面积约11.3×104 km2,盆地内已发现多个大中型油气田,为一富烃盆地[2022]图1a)。盆地具有高温(地温梯度4.0~4.5 ℃/100 m)、高压(最大压力系数2.3)、地层快速沉降和热液流体充注的特点[19]。地层自下而上依次发育中新统三亚组(N1s)、梅山组(N1m)和黄流组(N1h),上新统莺歌海组(N2y)及第四系乐东组(Qld[20]图1b)。

    莺歌海盆地南部乐东区黄流组致密砂岩储层(研究区A,图1a)发育重力流水道和海底扇沉积,是致密气勘探的主要层位[19,23],本文研究对象为重力流水道致密砂岩。根据Folk[25]的砂岩分类标准,黄流组砂岩主要为岩屑长石砂岩,次为长石石英砂岩。砂级碎屑组分中石英、长石、岩屑的相对含量分别为:石英含量介于68.0%~85.0%,平均值为79.8%,长石含量介于9.0%~19.3%,平均值为12.9%,岩屑含量介于3.4%~17.6%,平均值为7.3%。粒度为粗砂—中砂,分选磨圆较差,储层渗透率较低,非均质性较强。依据国家标准《GB/T 30501—2014致密砂岩气地质评价方法》,A区黄流组砂岩储层埋藏深度大(3 800~4 350 m),平均孔隙度为8.51%,平均渗透率为0.81×10-3 μm,属于致密砂岩储层。

  • 受海上钻井取心成本高和难度大的影响,乐东区黄流组储层岩心样品较少。选取13块典型柱状样品(乐东区A井黄流组,深度介于4 165~4 175 m)和16块典型块状样品(乐东区A井,深度介于4 165~4 175 m,乐东区C井,深度介于3 632~3 636 m)进行薄片鉴定、场发射扫描电镜、孔渗测量、高压压汞测试分析。根据Folk[25]的砂岩分类标准,A井样品均为岩屑长石砂岩,3种砂级碎屑组分中,石英平均相对含量为75.1%,长石为14.2%,岩屑为10.8%。填隙物包括碳酸盐胶结物、硅质胶结物、泥质杂基、黄铁矿等,碳酸盐胶结物含量高、非均质性强,铁方解石在碳酸盐胶结物中占比最高(平均为75.0%)。砂岩分选较差—差、磨圆中等—较差,砂岩内中粒—粗粒的颗粒占比约70%,依照Folk[26]划分标准样品为中砂岩。高压压汞实验按照GB/T 29171—2012《岩石毛管压力曲线的测定》进行,实验在AutoPore Ⅳ 9505孔隙分析仪上完成,实验温度为25 ℃,最大进汞压力为200 MPa,对应孔喉半径为0.004 μm。

  • 分形理论是根据不规则形体的自相似性来研究其内部结构的一种方法[27]。前人研究发现,分形理论可应用于砂岩、碳酸岩、泥页岩等复杂岩性的孔隙结构表征中[2829]。利用分形维数D可定量表征储层孔隙结构的复杂程度和不规则程度,D值一般介于2~3[2930]。分形维数越小,即数值越接近于2,表明孔隙形状越规则、孔隙表面越光滑,储层类型越好[14,28],因此利用分形维数可定量反映致密储层孔隙结构特征及复杂性。

    由于高压压汞实验在致密砂岩储层孔隙结构评价中更为常用[28],因此利用高压压汞曲线计算乐东区黄流组致密砂岩储层分形维数,进行储层孔隙结构评价。虽然分形维数存在多种计算模型,但是这些模型对于储层孔隙结构的非均质性和复杂程度的表征意义是相同的[14,29,31]

    依据几何原理计算分形维数的计算公式表示为[27]

    N>r=rrmaxPrdr=ar-D (1)

    式中:r为孔隙半径(μm);N为孔隙半径大于r的孔喉数量;rmax为最大孔隙半径(μm);P(r)为孔隙半径的密度分布函数;a为常数系数(a=1为管状孔隙模型,a=4π3为球状孔隙模型);D为分形维数[2729]

    根据Washburn[32]方程,利用高压压汞曲线可求出孔隙半径r:

    r=-2σcosθPc (2)

    式中:σ为空气与汞之间的表面张力(N/m);θ为汞润湿角(°);Pc为进汞压力(MPa)。汞为非润湿相,σ一般取0.48 N/m,θ为140°[13,28,32]

    结合压汞曲线,储层分形维数计算公式可表示为:

    Sw=(PcPmin)D-3 (3)
    Sw=1-SHg (4)

    对(3)式进行对数变换,并将(4)式带入(3)式中,可得出基于高压压汞曲线的分形维数计算公式:

    lg(1-SHg)=(D-3)lgPc-(D-3)lgPmin (5)

    式中:Pc为进汞毛管压力(MPa);Pmin为最大孔隙半径对应的毛管压力(MPa);Sw为各毛管压力对应的润湿相饱和度(%);SHg为累计进汞饱和度(%)[13,2829]。在(5)式中,lg(1-SHg)和lgPc可以利用高压压汞实验获得,参数D-3为lg(1-SHg)与lgPc线性相关的斜率,进而求取分形维数(D)。

  • 黄流组储层主要发育碳酸盐胶结作用、溶蚀作用、黏土矿物胶结作用和压实作用(图2a~d’)[33]。砂岩储层的成岩作用特征具有明显差别,根据成岩作用的差异性可以分为四种类型的成岩相。

    第一种成岩相中方解石胶结物发育嵌晶结构(图2a),具有半自形晶形态(图2a’),颗粒间为不接触—点接触,分选较差,磨圆中等,胶结物占据孔隙空间,溶蚀作用很弱,为强胶结成岩相。第二种成岩相中局部发育铁方解石胶结物(图2b),溶蚀作用较弱,孔喉中发育丝状伊利石(图2b’),颗粒间为线接触,分选较差,磨圆中等,为弱胶结—弱溶蚀成岩相。第三种成岩相中长石与岩屑发生强烈溶蚀(图2c,c’),碳酸盐胶结物不发育,颗粒间为线接触,分选较差,磨圆中等,为强溶蚀成岩相。第四种成岩相不发育碳酸盐胶结物,溶蚀作用较弱,颗粒间为凹凸接触(图2d),孔隙中发育蜂窝状伊利石(图2d’),压实作用较强,分选中等,磨圆较好,为强压实成岩相。不同的成岩作用导致了孔喉类型的差异性。

  • 根据铸体薄片和场发射扫描电镜观察,乐东区黄流组致密砂岩储层主要发育残余粒间孔(图2e)、粒间溶蚀孔(图2e,g)、铸模孔(图2f)、生物格架溶蚀孔(图2g,j)粒内溶蚀孔(图2h)、极少量晶间孔(图2k)。喉道类型主要包括弯片状喉道(图2e)、束状喉道(图2f)、管束状喉道(图2i)三类。储层内发育顺层微裂缝(图2l)。

    黄流组储层中的残余粒间孔常与溶蚀孔伴生,溶蚀孔隙是酸性流体与岩石中易溶组分作用的产物,多见长石溶蚀孔、岩屑溶蚀孔和生物格架溶蚀孔(图2e~g,j),长石多沿解理缝发生溶蚀(图2j),发育少量铸模孔,少见碳酸盐胶结物溶蚀孔发育。粒内溶蚀孔为长石、岩屑等矿物差异溶蚀形成,孔隙粒径较小(图2h)。晶间孔与自生矿物的生长或沉淀密切相关[1],如碳酸盐胶结物晶间孔、黄铁矿晶间孔等(图2k)。黄流组黏土矿物以伊利石为主(图2b’,d’),多堵塞喉道空间。喉道类型同样受成岩作用影响,刚性矿物含量越多压实作用越弱,弯片状—束状喉道发育(图2e,f),酸性流体进入孔隙所受的毛细管阻力小,溶蚀作用较发育;胶结物大量发育,或压实作用较强,喉道多细窄弯曲,为管束状喉道形态(图2i)。

    储层质量与孔喉类型存在明显规律,储层质量越好,残余粒间孔越多,溶蚀孔隙越发育,弯片状喉道越发育。而致密储层往往受到了强烈的胶结作用或者压实作用,酸性流体难与易溶组分充分接触,溶蚀孔不发育。

  • 高压压汞实验中的进汞曲线可以反映孔喉连通情况、孔喉分布特征等[34]。黄流组致密砂岩储层物性变化较大,13个典型样品的孔隙度介于2.06%~11.76%,平均值为7.18%;渗透率介于(0.09~1.26)×10-3 μm,平均值为0.50 ×10-3 μm。进汞曲线为“斜直型”(图3a),排替压力越小平台区间越明显,大孔喉的比例更多(图3b),表明分选性越好的储层孔喉半径越大、连通性越好。最大进汞饱和度介于68.80%~96.20%,排替压力介于0.14~2.75 MPa,平均孔喉半径介于0.08~1.10 μm,随着储层物性变差,排替压力增大、平均孔喉半径变小,汞进入孔喉空间需克服的毛细管力增大(图4)。

    孔喉半径呈双峰分布(图3b),储层类型越好,大孔喉占比越高。在致密储层中,虽然小孔喉占比较高,但是大孔喉对渗透率的贡献值可达90%。

  • 通过计算黄流组致密储层样品的分形维数D(计算方法见本文2.2),可定量评价储层孔喉结构的复杂程度,辅助致密储层孔隙结构特征的研究。

    其中lgSHg-lgPc曲线的线性拟合关系的斜率为D-3,进而计算出分形维数数值。其中SHg<5%的部分受样品不平整的影响,不能反映真实的孔喉空间特征。部分样品发育较多连通孔喉,SHg可高于95%,但当SHg>95%时进汞压力迅速增大,破坏毛细管阻力。因此选取SHg在5%~95%的实验数值进行研究。黄流组致密储层的孔喉半径为两段式分布(图3b),受其影响,进汞曲线常具有分段性特征[14]。分别计算了整体分形维数D,相关系数为R图5a、表1);分段的分形维数Dmax(大孔喉分形维数)、Dmin(小孔喉分形维数),相关系数分别为RminRmax图5b、表1)。

    样品深度/m大孔喉半径峰值/μm分界点的半径值/μmDDmaxDminΦmax/%Φmin/%Φwi/%Φ/%
    XL14 165.850.250.0152.562.612.287.580.071.949.59
    XL24 166.350.250.0532.722.832.471.240.061.883.19
    XL34 166.760.250.0212.632.722.233.890.052.346.28
    XL54 167.450.160.0422.752.762.702.160.093.015.26
    XL64 168.150.630.0152.592.612.328.420.071.5310.02
    XL84 169.320.630.0212.802.882.440.850.081.302.23
    XL94 169.520.630.0272.602.562.669.290.072.4011.76
    XL104 170.510.630.0272.572.582.488.980.032.6511.66
    XL124 171.010.250.0152.682.742.331.240.030.802.06
    XL144 172.501.000.0182.802.832.671.360.031.272.67
    XL154 172.771.600.2682.782.712.834.980.263.508.73
    XL164 173.370.630.0362.602.632.497.600.112.169.87
    XL174 174.001.000.0672.552.572.487.850.231.9910.06

    D值介于2.55~2.80,平均值为2.66,与渗透率和孔隙度呈负相关(图6a)。Dmax是压汞曲线前半段的分形维数,进汞压力小,代表大孔喉的分形特征,值介于2.56~2.88,平均值为2.69;Dmin是压汞曲线后半段的分形维数,进汞压力大,代表小孔喉分形特征,值介于2.13~2.83,平均值为2.48。其中Dmax值与孔隙度、渗透率的相关性较强(图6b),且优于D值,而Dmin值与孔渗关系较差(图6c),表明大孔喉的孔隙结构是影响致密砂岩储层储集和渗流能力的重要因素之一。R的平均值为0.97,Rmax的平均值为0.99,Rmin的平均值为0.98,分段拟合的回归关系相较于整段拟合更好,因此DmaxDmin参数具有实际意义,孔隙结构分级评价是有必要的。

    lgSHg⁃lgPc图中前后两段线性拟合曲线的交点对应的孔喉半径为分界点的半径值,前人研究表明分界点的半径与孔喉峰值半径近乎相等[10]。依据黄流组储层孔隙结构特征,结合分形维数进行孔喉结构分级评价。分界点的半径值将储层孔隙结构分为两种类型,大孔喉的孔喉半径大于分界点半径值,孔隙度为Φmax;小孔喉的孔喉半径小于分界点半径值,孔隙度为Φmin,汞在高驱动力下可以进入;汞未能进入的孔喉空间不赋存可动流体,为死孔喉,孔隙度为Φwi,样品总孔隙度为Φ表1)。不同规模孔隙度与分形维数均存在良好的相关性(图7a~c),其中Φmax与Dmax的相关性最好,相关系数为0.907 2(图7a)。

  • 不同级次孔喉在储层中的分布存在明显差别,Φmax的平均值为5.03%(0.85%~9.25%),Φmin的平均值为0.09%(0.03%~0.26%),Φwi的平均值为2.06%(0.80%~3.50%)。Φmax与孔隙度和渗透率均明显正相关(图7d),Φmin仅与渗透率相关性较强(图7e),Φwi与渗透率和孔隙度均为弱相关(图7f)。说明在致密储层中大孔喉越多储层物性越好(表1)。连通的小孔喉空间,不仅占比较少,对孔渗的影响也有限,这部分孔喉对储层物性的影响较低。

    致密砂岩储层中流体的渗流能力是评价储层有效性的关键,不同级别孔喉对储层的渗流能力的影响存在差异。DDmax与孔隙度和渗透率均呈负相关关系(图6a,b),分形维数越大,致密储层的孔隙结构越复杂,储层物性越差。致密砂岩储层经历了多期减孔的成岩作用,孔喉细小,类型多样,但优质储层受溶蚀作用或早期碳酸盐胶结物支撑作用的影响,储层孔喉空间较大,细小复杂的孔喉类型发育较少,分形维数接近于2。Dmax值越大,Φmax越小(图7a),但是Dmin值越大,ΦminΦwi越大(图7b,c)。孔隙结构越复杂,储层中连通的大孔喉空间越少,细小的喉道增加了不可动孔隙空间的占比,小孔喉和孤立孔喉的含量略有增长。

  • 对致密砂岩储层孔隙结构进行分级评价,首先要确定孔隙结构的分级标准是否有实际意义。图8a表明,压汞分形的分界点半径值与Φmin呈正相关,即两段式压汞分形分界点与连通的大小孔喉存在联系,即分界点半径值越大,连通的小孔喉越多。ΦmaxDmaxΦmax与孔渗的相关性较高(图7a,d),大孔喉可以更有效地表征储层质量和孔喉结构的复杂程度。

    根据分形理论,当一个对象二向等比例延展,分形维数为2,三向等比例延展时,分形维数则为3,分形维数的变化可以反映孔隙结构特征及差异[10,35]Φmax占孔隙总体积越小,Dmax越大(图8b),储层平均孔喉半径越小(图8c),储层孔隙结构特征越接近三向等比例延展孔喉模型,喉道更细小狭长。

    根据致密砂岩储层的孔喉半径、成岩作用、分形维数特征(图9[33],将莺歌海盆地A区黄流组储层划为四种类型。

    类型Ⅰ为小孔喉优势型致密储层,大孔喉孔隙度占比小于45%,D值为2.7~2.8,Dmax值为2.75~2.9,孔喉半径分布曲线为双峰型小孔喉优势(图9a),碳酸盐胶结物异常发育,溶蚀作用较弱,多发生在易溶组分边缘,溶蚀矿物包括钙质生物格架、长石、岩屑,为强胶结成岩相(图9e)。孔喉半径中值较小(图8c),孔喉复杂程度高,为微孔极细喉型,喉道细窄弯曲(图9i),喉道与孔隙多单点连接,发育孤立孔隙,孤立点—单点连接束状喉道形态(图9m)。

    类型Ⅱ为大—小孔喉连续型低渗储层,大孔喉孔隙度占比45%~70%,D值为2.6~2.8,Dmax值为2.7~2.85,孔喉半径分布曲线为双峰型无明显优势,孔喉半径分布较连续(图9b)。碳酸盐胶结物较发育,溶蚀作用较弱,多为岩屑长石发生溶蚀,为弱胶结—弱溶蚀成岩相(图9f)。孔喉半径中值变化较大(图8c),孔喉复杂。孔隙半径较大但数量有限,喉道较弯曲(图9j),喉道与孔喉呈单点或多点连接,少发育孤立孔隙,单点—多点连接弯片状喉道形态(图9n)。

    类型Ⅲ为大孔喉优势型优质储层,大孔喉孔隙度占比大于70%,D值为2.55~2.6,Dmax值为2.55~2.65,孔喉半径分布曲线为双峰型大孔喉优势(图9c)。砂岩内胶结物不发育,原生粒间孔和溶蚀孔隙发育,岩屑长石溶蚀作用强烈,强溶蚀成岩相(图9g)。孔喉半径中值偏大,但变化较大(图8c),喉道短而粗,孔喉复杂程度较低。孔隙半径较大且数量多,喉道较粗(图9k),喉道与孔隙为多点连接,几乎不发育孤立孔隙,网状连接粗喉形态(图9o)。

    类型Ⅳ为大孔喉单峰型低渗储层,大孔喉孔隙度占比50%~60%(图8b),D值为2.7~2.8,Dmax值为2.65~2.75,孔喉半径分布曲线为单峰型(图9d)。砂岩中胶结物不发育,杂基含量较高,储层强烈压实,发育粒间溶蚀孔,强压实成岩相(图9h)。压汞曲线仅反映连通的大孔喉,孔喉半径中值较高(图8c)。受压实作用和黏土矿物堵塞喉道的影响,喉道狭窄弯曲,毛细管作用下可动流体空间有限(图9l),喉道与孔隙为多点连接管束状喉道形态(图9p)。

  • Fisher判别是将m维空间的变量组合投影到维数较低的n维空间中,然后在较低的n维空间再进行分类,使每一类的类内离差尽可能小,组间离差尽可能大[36]。因此利用统计学Fisher判别的方法,可将高维空间的参数降至二维空间,并在二维空间中定义类型划分的界限值。不同级次储层在孔隙结构特征、物性、成岩作用类型、分形维数等方面存在明显差异,因此依据渗透率、孔隙度、Dmax参数,通过Fisher判别可对储层类型进行划分与预测。

    以13块岩心样品的储层分类为基础(图9),建立Fisher判别函数模型(F1、F2,公式6,7)。根据F1值、F2值的分布特征,确定各级次储层的界限值,最终结果如图10所示。由于Ⅳ类储层(大孔喉单峰型低渗储层)仅有一个样品点(XL15),且样品孔喉结构的非均质性强,虽然Φwi含量较高(表1),但孔渗较好,利用Fisher判别难以确定Ⅳ类储层与Ⅲ类储层的界线。Ⅳ类储层中杂基与黏土含量较高,在自然伽马曲线(GR)中具有偏大的尖峰形态,因此认为Ⅳ类储层为:F1>0,GR为尖峰形态,呈薄层发育在砂岩内部。储层评价的划分标准见表2所示。

    储层类型Ⅰ类储层Ⅱ类储层Ⅲ类储层Ⅳ类储层
    F1<0<0>0>0
    F2>0.5<0.5
    测井响应自然伽马具有尖峰形态
    F1=0.452Φ+1.637k-5.515Dmax+10.799 (6)
    F2=0.498Φ+3.563k-29.108Dmax-83.791 (7)

    根据测井曲线响应特征,建立F1、F2的测井预测模型(公式8,9),依据不同级次储层的F1、F2的划分标准和自然伽马曲线特征,预测储层类型,为储层质量和储层内气水关系的评价奠定基础(图11)。

    F1=-18.872DEN-17.606AC-18.199Rt+26.663 (R2=0.61) (8)
    F2=-13.854GR-7.844DEN+8.635AC+9.014 (R2=0.44) (9)

    式中:DEN为密度测井,g/cm3;AC为声波时差测井,μs/ft;Rt为电阻率测井,Ω·m;GR为自然伽马测井,API。

  • 致密砂岩储层的渗流能力是评价储层有效性的关键参数之一[1]。储层的排替压力、平均孔喉半径、分形维数等与渗透率存在良好的相关关系(图4a,b、图6),其中分形维数与孔隙度存在相关性(图7a~c),大孔喉空间的复杂程度对储层的渗流能力存在影响(图7a),孔喉空间的发育规律与储层成岩作用密不可分(图9)。储层孔隙结构特征对含气性存在明显影响。

    由于气藏内气水关系不仅受储层质量的影响,还与构造部位、泥岩隔夹层、天然气运移动力等相关。为减少除储层类型以外因素的影响,砂体内部储层分级类型与储层气水分布情况进行分析(以A井黄流组二段H2-Ⅱ、H2-Ⅲ砂组为例)。

    研究区黄流组重力流水道砂岩中的主要矿物成分相对含量为(全岩X衍射实验数据来自中海石油(中国)有限公司海南分公司):石英含量介于36.0%~88.0%,平均值为58.5%,长石含量介于6.0%~23.0%,平均值为13.0%,碳酸盐胶结物含量介于0~40.0%,平均值为19.2%,黏土矿物含量介于1.0%~19.0%,平均值为9.3%。刚性矿物约占90%,塑性黏土矿物含量较低,强压实成岩相成因的Ⅳ类储层在研究区较不发育,对储层气水分布的影响较小。但Ⅳ类储层可以作为低渗层对气层进行封隔(图11,4 060~4 090 m)。在图11中可看出Ⅲ类储层较相邻其他类型储层,气测响应增强,尤其当Ⅲ类储层在砂岩顶部发育时(图11,4 060~4 070 m),储层含气饱和度明显增大,Ⅱ类储层、Ⅰ类储层中气测响应逐渐降低,表明喉道越细小狭窄、孔喉连通节点越少、大孔喉复杂程度越高、孔隙空间越小(图9),致密砂岩储层含气量越低。在Ⅰ类储层较发育段,虽然储层含气饱和度约为50%,但储层含气量较低,产能较差(图11,4 120~4 130 m)。综上所述,Ⅲ类储层储集能力和渗流性能力强,储层产气效能高,具有良好的勘探价值,Ⅳ类储层可作为Ⅲ类储层内遮挡层,Ⅰ类储层致密,储集能力有限。因此,利用储层分级评价模型,可为致密砂岩储层产能评价提供新的研究思路。

  • (1) 莺歌海盆地乐东区黄流组致密砂岩储层的孔喉半径越大、连通性越好,大孔喉发育,分形维数越接近2。Dmax值与孔渗的相关性最强,大孔喉的孔隙结构特征是影响致密砂岩储层储集能力和渗流能力的重要因素之一。基于压汞曲线和分形理论将致密砂岩划分为大孔喉、小孔喉、孤立孔喉三个级次,其中大孔喉的孔隙度与孔渗关系最好。

    (2) 建立了致密砂岩储层分级评价的四种模型:类型Ⅰ为小孔喉优势型储层,强胶结成岩相,大孔喉孔隙度占比小于45%,D值为2.7~2.8,Dmax值为2.75~2.9,致密储层;类型Ⅱ为大—小孔喉连续型储层,弱胶结—弱溶蚀成岩相,大孔喉孔隙度占比45%~70%,D值为2.6~2.8,Dmax值为2.7~2.85,低渗储层;类型Ⅲ为大孔喉优势型储层,强溶蚀成岩相,大孔喉孔隙度占比大于70%,D值为2.55~2.6,Dmax值为2.55~2.65,优质储层;类型Ⅳ为大孔喉单峰型储层,强压实成岩相,大孔喉孔隙度占比50%~60%,D值为2.7~2.8,Dmax为2.65~2.75,低渗储层。

    (3) 利用储层渗透率、孔隙度、Dmax参数,通过Fisher判别方法,建立了储层类型测井预测模型。在相同地质背景条件下,Ⅲ类储层、Ⅱ类储层、Ⅰ类储层的气测响应逐渐降低,Ⅲ类储层储集能力和渗流能力强,储层产气效能高,具有良好勘探价值,Ⅳ类储层可作为砂体内遮挡层,Ⅰ类储层的储集能力有限。

    (4) 基于成岩作用、孔喉结构特征、分形理论可划分储层类型,储层的含气性特征与储层类型密切相关,研究储层孔隙结构特征具有重要意义。需要指出的是储层孔隙结构对气藏形成时含气性变化的影响还需进一步研究。

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