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三孔两渗煤层气产出建模及应用研究
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摘要
本文以煤层气地质学、渗流力学、分形理论及油气藏数值模拟等学科领域的理论为指导,采用物理模拟和数值模拟相结合的方法综合定量划分了三孔两渗模型孔裂隙系统,建立了三孔两渗模型渗流孔和裂隙系统储层参数的计算模型,并以沁水盆地QSDU01井为例进行三孔两渗模型排采表现模拟。通过工作,得到了如下的结论。
     基于压汞、核磁共振和液氮吸附实验分别划分了煤岩孔裂隙系统,并根据各实验的划分结果提出了煤岩孔裂隙系统的综合划分方法,结果表明扩散孔和渗流孔的分界点约为64nm,渗流孔和裂隙系统的分界点一般为600~700nm。分析孔裂隙系统与镜质组反射率的关系,认为扩散孔含量随煤阶的增加而增加,渗流孔含量随煤阶的增加而降低,而裂隙含量与煤阶的相关性较差。
     根据煤岩孔裂隙系统的综合划分结果,将各孔裂隙系统的孔隙度分为两类。第一类包括扩散孔可动孔隙度、渗流孔有效孔隙度和渗流孔不可动孔隙度,这类孔隙度对煤岩渗透率影响较低;第二类包括渗流孔可动孔隙度和裂隙可动孔隙度,这类孔隙度是影响煤岩渗透率的主要因素。进一步根据煤岩渗流孔和裂隙系统可动孔隙度的相对大小,将煤样分为裂隙主导渗透率煤样、渗流孔主导渗透率煤样和综合煤样。分别依据裂隙主导渗透率煤样和渗流孔主导渗透率煤样与渗透率之间的关系得到了修正的火柴棍模型和Coates模型,这两个模型可用于模拟渗流孔和裂隙系统的渗透率。
     参数敏感性分析结果表明渗流孔和裂隙系统均存在无效临界孔隙度,其值恒为0.1%,当低于此值时,渗流孔或裂隙系统对产水产气不起作用。两套渗流系统的产能耦合结果表明渗流孔流入裂隙的气量和水量分别控制了井筒产出的气量和水量特征。排采初期,储层压力降低的主导因素是裂隙产出的水量,但随排采进行,渗流孔产出的水造成的压降越来越明显。煤层气产能的第一个峰值受控于气体解吸,而第二个峰值则取决于渗流孔流入裂隙的气量特征。
     QSDU01井的储层参数动态可分为两个阶段。第一阶段为排采前310天,本阶段各参数的降幅均较小;第二阶段为排采310天之后,这一阶段储层压力逐渐降至临界解吸压力以下,含气量动态曲线也开始大幅降低,孔隙度和渗透率主要受有效应力增大负效应的影响而逐渐降低,但降幅较小。
     最后,基于三孔两渗模型的模拟结果,本文建立了三孔两渗产能预测模型。
Based on the theory of coalbed methane geology, seepage mechanics, fractaltheory and numerical simulation for oil and gas reservoir, this paper proposed acomprehensive classification method for identifying migration pore, permeation poreand fracture, established models for calculating reservoir parameters of permeationpore and fracture, and finally took well QSDU01in Qinshui basin as an example tosimulate its drainage performance under triple porosity/dual permeability (TPDP)model. The following cognitions are obtained.
     Based on the classification results of coal pore systems under mercury intrusionporosimetry (MIP), nuclear magnetic resonance (NMR) and nitrogen adsorption underlow temperature (NALT), a comprehensive classification method for identifying coalpore systems is proposed. The results show that the dividing radius of migration poreand permeation pore is about64nm, and the dividing radius of permeation pore andfracture is about600~700nm. The results also indicate that the volumetric proportionof migration pore increases along with vitrinite reflectance increasing, that ofpermeation pore decreases with vitrinite reflectance increasing, and fracture contenthas little relationship with vitrinite reflectance.
     Porosity of different pore systems can be arranged into two types. The first typeincludes irreducible porosity of each pore system, and this type has little impact onpermeability. The second type represents reducible porosity of permeation pore andfracture, and this type is the main fact influencing coal permeability. Coal samples canbe divided into three types based on the relative amount of porosity of permeationpore and fracture, and they are fracture-dominated samples, permeation-dominatedsamples and hybrid samples. The modified matchstick and Coates models can then beestablished by fitting porosity of fracture-dominated and permeation-dominatedsamples with permeability, respectively. The two models can be used to predictpermeability of permeation pore and fracture systems.
     Historical matching under TPDP and dual porosity/single permeability modelsfor well QSDU01indicates that the TPDP model is more suitable for describing CBMflow process. Sensitivity analysis indicates that porosity has a negative influence ongas production, and the negative influence vanishes if porosity is lower than0.1%.Hence, invalid critical porosity is defined, of which constant value is0.1%.
     Gas and water linkages of permeation pore and fracture systems reveal that the features of gas and water transmitted from permeation pore to fracture control theperformances of gas and water output from well bore respectively. Drainage offracture water is the main reason for reservoir pressure decreasing at the early stage,while the output of water of permeation pore system becomes more and moreimportant as the drainage processing. The first peak of gas production is controlled bydesorption gas from desorption pore system, and the second peak is influenced by thegas transmitted from permeation pore to fracture system.
     Drainage performance simulation under TPDP model shows that the drainageperiod for well QSDU01can be divided into two parts. The first part refers the earlier310days, of which the reservoir parameters change a little. The second part refers thetime after310days, when reservoir parameters decrease rapidly.
     Finally, a gas production prediction model is established under TPDP model.
引文
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