基于神经网络算法的井下裂缝诊断与堵漏技术

在钻井过程中,常常钻遇不同宽度的井下地层裂缝。钻遇裂缝时容易发生钻井液漏失现象,甚至发生钻井液失返现象,严重影响了安全、高效钻井。目前裂缝封堵的方法常存在封堵成功率不高、堵漏承压能力低的问题,其中一个重要的原因是对井下地层的裂缝宽度等特征认识不清。基于地层裂缝产生的岩石力学机理,确定影响裂缝宽度关键的6个力学和工程因素,并利用神经网络计算的非线性、大数据特点建立了井下地层裂缝宽度的分析模型,模型包含输入层、输出层和3个隐藏层。通过该模型诊断井下裂缝宽度,提高了计算精度,平均误差仅为2.09%,最大误差为5.88%,解决钻井现场仅凭经验判断裂缝误差较大和依靠成像测井成本较高的问题。同时根据神经网络模型诊断得到的裂缝宽度优化堵漏材料的粒径配比,提高了裂缝内的架桥封堵强度和架桥的稳定性,封堵层的承压能力达到12.8 MPa,反向承压能力达到4.5 MPa。现场堵漏试验最高憋压10 MPa,经过封堵作业后大排量循环不漏,达到了裂缝性地层高效堵漏的目的,堵漏一次成功。 

Downhole Fracture Diagnosis and Mud Loss Control Technologies Bases on Neural Network Algorithm

Formation fractures of different widths are always met during drilling, resulting in partial mud losses or even lost return which seriously affect drilling in a safe and efficient manner. Presently, the success rate of controlling mud losses into fractures is not high, and the fractures plugged have low pressure bearing capacities. One cause to these problems is the lacking of understanding of the widths of the fractures into which mud is lost. In this paper, rock mechanics mechanisms of formation fracture generation are used as the bases to determine the 6 mechanical and engineering factors affecting the width of fractures produced downhole. Using the nonlinearity and big data analysis natures of neural network computation a model for analyzing the widths of downhole formation fractures was established, which included input layer, output layer and 3 hidden layers. Using this model, the calculation precision of diagnosing the widths of downhole fractures was improved to an average error of only 2.09% and the maximum error of 5.88%, resolving the problem of predicting fracture width through experiences which is inaccurate or through imaging logging which is expensive. The widths of fractures calculated with the model were also used to optimize the particle size distribution of plugging additives, helping improve the strength and stability of bridging inside the fractures, the pressure bearing capacity of the plugged fractures was increased to 12.8 MPa and the back-pressure bearing capacity to 4.5 MPa. In field application, the highest pressure squeezed on the plugged fractures was 10 MPa, and the plugged fractures were able to stand large flow rate circulation, indicating that the fractured formations were effectively and successfully plugged.