何旭晟,周井红,管桐,代红,魏攀峰,潘孝青. 地质工程原生数据预测深层小尺度裂缝性地层漏失特征[J]. 石油钻采工艺,2024,46(1):33-44. DOI: 10.13639/j.odpt.202404005
引用本文: 何旭晟,周井红,管桐,代红,魏攀峰,潘孝青. 地质工程原生数据预测深层小尺度裂缝性地层漏失特征[J]. 石油钻采工艺,2024,46(1):33-44. DOI: 10.13639/j.odpt.202404005
HE Xusheng, ZHOU Jinghong, GUAN Tong, DAI Hong, WEI Panfeng, PAN Xiaoqing. Prediction of loss characteristics in deep small-scale fractured formations using geological engineering native data[J]. Oil Drilling & Production Technology, 2024, 46(1): 33-44. DOI: 10.13639/j.odpt.202404005
Citation: HE Xusheng, ZHOU Jinghong, GUAN Tong, DAI Hong, WEI Panfeng, PAN Xiaoqing. Prediction of loss characteristics in deep small-scale fractured formations using geological engineering native data[J]. Oil Drilling & Production Technology, 2024, 46(1): 33-44. DOI: 10.13639/j.odpt.202404005

地质工程原生数据预测深层小尺度裂缝性地层漏失特征

Prediction of loss characteristics in deep small-scale fractured formations using geological engineering native data

  • 摘要: 中江-蓬莱气区筇竹寺组地层是典型的深层裂缝性地层,钻前漏点垂深、具体漏速等不清楚,现有堵漏手段匹配性差,漏失处理消耗工时偏高。为此,利用从现场录井、测井、钻井等历史数据中提取地质工程可以测量的信息138项,计算全部因素对漏速的影响特征系数,采用削元法筛选漏失主控因素16项。室内模拟地层裂缝尺度0.008~0.130 mm时,测试6项钻井液性能主控因素对漏速的影响特征系数范围与矿场计算特征系数范围一致,该裂缝尺度超过岩心观察范围,分析存在裂缝摩滑效应。优选粒径0.001~0.010 mm纳米活性颗粒,室内测试密度2.24 g/cm3水基钻井液加质量分数0.1%~0.8%的颗粒时,宽0.008 mm裂缝内钻井液漏失摩阻提高了0.01~0.16 MPa;桥堵体系中加入质量分数0.1%~0.5%纳米活性颗粒后,宽0.008~0.140 mm裂缝承压提高至7.2~10.9 MPa,改善堵漏效果可行。现场开展2井次漏点预测,实际漏点预测率80%,预测垂深偏差不大于31 m,相对传统方法提升明显。2井次中累积完成5次堵漏,一次堵漏成功率80%,单次漏失处理消耗工时28.25~39.15 h,均值32.39 h,相对已作业井下降68.60%。结果表明,地质工程原生数据预测深部小尺度裂缝性地层漏失特征可行。

     

    Abstract: Gongzhusi group in Zhongjiang-Penglai gas province is typical deep fractured formation, with unknown vertical depth of leakage point before drilling and specific leakage rate. The existing plugging methods fail to solve the challenges in such formation, and the treatment lasts for long period. In view of this,138 geological engineering factors are extracted from the history data of logging and drilling, the characteristic coefficient of all factors on the leakage rate are calculated and 16 leakage control factors are screened out by the element reduction method. While the formation fracture scale for lab simulation is 0.008~0.130 mm, the contribution coefficient of 6 drilling fluid performance main control factors to the leakage rate is consistent with the on-site value. The test formation fracture scale exceeds the observation range of the core, and the analysis shows the friction and sliding effect of fracture. The nanometer active particles of 0.001~0.010 mm particle size are preferred. While the water base drilling fluid with density 2.24 g/cm3, adding mass fraction 0.1%~0.8% of particles, is tested, the leakage resistance of drilling fluid in the crack of 0.008 mm wide is increased by 0.01~0.16 MPa. After 0.1%~0.5% particles are added to the bridge plugging system, the pressure on wide 0.008~0.140 mm crack is increased to 7.2~10.9 MPa, showing feasible plugging effect. The leakage point prediction in 2 wells was carried out on site, with actual rate of 80%, and the predicted vertical depth deviation was no more than 31 m, indicating remarkable improvement compared to the traditional methods. Five plugging operations was performed in two wells, the success ratio reached 80%, and one single leakage treatment lasted for 28.25~39.15 h, with averaged value 32.39 h, decreased by 68.60% compared to the existing wells. The filed application shows that prediction of loss characteristics in deep small-scale fractured formations using geological engineering native data is feasible to improve the plugging efficiency.

     

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