A Method for Predicting Productivity of Sandstone Reservoirs Based on Permeability Synthesis Technology
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摘要: 利用常规测井资料准确计算钻杆地层测试(DST)渗透率,能够大幅提高海上非均质砂岩油藏产能预测精度。为此,综合考虑惠州凹陷宏观沉积成岩作用和微观孔隙结构对储层渗透率的影响,建立了不同类型储层绝对渗透率的测井解释模型。正演分析表明,射孔层段不同渗透率级差的储层对产能的贡献明显不同;对不同级别储层渗透率进行加权求和得到合成测井渗透率,并对权系数大小进行约束,突出优势储层对产能的贡献,建立了DST渗透率的回归拟合方程;采用差分进化算法进行迭代,得到DST渗透率计算方程的最优解。采用该方法对惠州凹陷72个油层产能进行预测,48个油层的产能大于100 m3/d,预测相对误差小于30%的油层占比90%;24个油层的产能为10~100 m3/d,相对误差小于50%的油层占比79%。研究结果表明,基于渗透率合成技术的砂岩油藏产能预测方法,能够为海上油田测试作业决策提供指导,降低勘探作业成本。Abstract: Using conventional logging data to accurately calculate the permeability of drill-stem test (DST) can greatly improve the accuracy of productivity predictions of offshore heterogeneous sandstone reservoirs. Based on this, the influence of sedimentary diagenesis and pore structure of Huizhou Sag on reservoir permeability were comprehensively considered from macroscopic and microscopic perspectives, respectively. In this work, a logging interpretation model of absolute permeability was built for different reservoir types. Forward analysis results show that reservoirs with different permeability contrast in perforated intervals have significantly different contributions to productivity.The synthetic logging permeability was calculated by weighted summation of permeability at different levels of the reservoir, and the weight coefficient was constrained to highlight the contribution of favorable reservoirs to productivity. An iterative analysis was performed with a differential evolution algorithm to yield the optimal solution of the equation. This method has been applied in 72 oil layers in Huizhou Sag for productivity prediction. The productivity from 48 layers was found greater than 100 m3/d, and the proportion of layers whose relative prediction errors within 30% was 90%. In addition, 24 layers had the productivity of 10–100 m3/d, among which the layers whose relative error was less than 50% accounted for 79% of the oil layers. This study indicates that the productivity prediction method based on permeability synthesis technology can guide the decision-making of offshore field tests and operations to reduce the exploration cost.
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Key words:
- logging /
- permeability /
- synthesis technology /
- productivity prediction /
- DST permeability /
- Huizhou Sag
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表 1 惠州凹陷不同油藏类型的供油半径计算模型
Table 1. Calculation models of oil supply radius for different reservoir types in Huizhou Sag
油藏类型 供油半径计算模型 相关系数 油藏内部发育断层 $ {r_{\text{e}}}{\text{ = 29}}{\text{.883}} \left(\dfrac{{{K_{{\text{DST}}}}}}{\mu }\right){^{0.499\;2}} $ 0.975 9 边水驱动油藏 ${r_{\text{e}}}{\text{ = 41}}{\text{.321}} \left(\dfrac{{{K_{{\text{DST}}}}}}{\mu }\right){^{0.443\;8}} $ 0.927 7 底水驱动油藏 $ {r_{\text{e}}}{\text{ = 4}}{{.629\;9}}\left(\dfrac{{{K_{{\text{DST}}}}}}{\mu }\right){^{0.706\;3}} $ 0.853 9 表 2 惠州凹陷不同储层类型的孔、渗模型和Fisher识别结果
Table 2. Porosity and permeability models and Fisher identification results of different reservoir types in Huizhou Sag
储层类型 岩性 沉积微相 渗透率计算模型 相关系数 Fisher识别结果 符合 不符合 PF1 中、粗砂岩,含砾砂岩 辫状分流河道、滩砂水道和沿岸坝 $K = 2.473\;6{{\rm{e}}^{0.309\;6\phi }}$ 0.82 60 5 PF2 中—细砂岩 分流河道、河口坝和风暴席状砂 $K = 0.411{{\rm{e}}^{0.335\;1\phi }}$ 0.91 210 11 PF3 钙质中—细砂岩 潮汐水道、远砂坝 $K = 0.000\;06{{\rm{e}}^{0.636\;2\phi }}$ 0.83 28 0 PF4 细砂岩、粉砂岩 远砂坝 $K = {10^{ - 9.045}}{\phi ^{8.402}}$ 0.84 39 8 PF5 泥质粉砂岩 分流河道间湾、远砂坝 $K = 0.004\;7{{\rm{e}}^{0.403\;7\phi }}$ 0.79 16 4 表 3 惠州凹陷储层分级标准
Table 3. Reservoir classification standard of Huizhou Sag
储层
级别孔隙度,% 渗透率/
mD米采油指数/
(m3·d−1·MPa−1·m−1)产量分类 Ⅰ级 ≥30.0 ≥2 000 10.50~163.90 高产 Ⅱ级 25.0~30.0 500~2 000 6.80~62.50 高产 Ⅲ级 20.0~25.0 200~500 4.10~21.60 中—高产 Ⅳ级 17.5~20.0 50~200 0.92~11.25 中—低产 Ⅴ级 15.0~17.5 20~50 0.87~3.65 中—低产 Ⅵ级 12.0~15.0 5~20 0.47~1.78 低产—少产 Ⅶ级 <12.0 <5 0.02~0.54 少产—无产 -
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