基于确定性和随机模型的薄储层岩性预测
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摘要
三角洲前缘地区一直是油气勘探的重点,但大多数情况下砂泥岩波阻抗值重叠,而且薄砂层较多,地震数据反演结果达不到分辨薄层的精度,致使无法准确预测砂体分布规律。从综合利用不同储层建模技术各自优势识别薄砂层的思路出发,针对三角洲前缘地区的特点提出了确定性建模和随机建模联合的方法,即首先用确定性建模得到声波波阻抗,在此基础上用随机模拟方法得到薄砂层的展布。采用的具体方法为地震与测井联合反演方法及马尔可夫链随机模拟方法,随后按照此方法对松辽盆地北部Y地区进行了试验,最终得到更为准确的薄砂体预测结果。
The delta front is always one of the focuses for oil and gas exploration.However,reservoirs in delta front commonly occur as thin sandstone layers,which cannot be recognized accurately for the low resolution of seismic inversion,hence the distribution pattern of sandbodies could not be accurately predicted,leading to the difficulties for exploration and production.Taking advantage of various reservoir modeling techniques,this paper puts forward a new methodology of joint deterministic-stochastic modeling for lithology prediction of thin reservoirs in delta front areas.It first obtains acoustic impedance through deterministic modeling,and then predicts distribution of thin reservoirs through stochastic modeling.The specific methods used are joint seismic-log inversion and Markov chain modeling.Case study in the Y block of the northern Songliao Basin shows that more accurate prediction of thin sand layers could be achieved.
The delta front is always one of the focuses for oil and gas exploration.However,reservoirs in delta front commonly occur as thin sandstone layers,which cannot be recognized accurately for the low resolution of seismic inversion,hence the distribution pattern of sandbodies could not be accurately predicted,leading to the difficulties for exploration and production.Taking advantage of various reservoir modeling techniques,this paper puts forward a new methodology of joint deterministic-stochastic modeling for lithology prediction of thin reservoirs in delta front areas.It first obtains acoustic impedance through deterministic modeling,and then predicts distribution of thin reservoirs through stochastic modeling.The specific methods used are joint seismic-log inversion and Markov chain modeling.Case study in the Y block of the northern Songliao Basin shows that more accurate prediction of thin sand layers could be achieved.
引文
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2李军,郝天珧.油气储层随机模拟方法综述[J].地球物理学进展,2006,21(2):458～464
3刘振峰,郝天珧,杨长春.沉积模型和储层随机建模[J].地球物理学进展,2003,18(3):519～523
4Li W,Li B,Shi Y.Markov-chain simulation of soil textural profiles[J].Geoderma,1999,92:37-53
5Carle S F,Fogg G E.Modeling spatial variability with one and multi-dimensional continuous Markov chains[J].Mathematical Geology,1997,29(7):891-917
6Elfeki A,Dekking M.A Markov chain model for subsurface char-acterization:Theory and applications[J].Mathematical Geology,2001,33(5):568-589
7范洪军,李军,肖毓祥,等.地震分频技术在扇三角洲演化过程中的应用[J].石油与天然气地质,2007,28(5):682～686,692
8胡水清,韩大臣,夏专庄.高含水期地震约束储层建模技术[J].石油与天然气地质,2008,29(1):128～134
9穆星.稀疏脉冲波阻抗反演参数对反演效果的影响研究[J].工程地球物理学报,2005,2(2):104～108
10刘振峰,郝天珧,方辉.用Markov链模型随机模拟储层岩相空间展布[J].石油学报,2005,26(5):57～60
11盛骤,谢式千,潘承毅.概率论与数理统计[M].北京:高等教育出版社,2002:354～367
12李汉林,赵永军.石油数学地质[M].东营:石油大学出版社,1998:247～253
13Schwarzacher W.Repetitions and cycles in stratigraphy[J].Earth Sci Rev,2000,50:51-75
14李军,郝天珧,刘建,等.基于不同邻域系统的马尔可夫链模型的储层岩相随机模拟[J].现代地质,2006,20(4):621～627
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