Bit dullness grading using a handheld device

为了获取地下资源，无论是碳氢化合物的回收，矿物的勘探，还是获取地热储量，都必须从地表钻孔。 在各个行业中使用的常见类型的钻头是刮刀钻头，其具有卡宾枪或钢主体以及由多晶金刚石复合片（PDC）制成的刀片。 这些钻头通常暴露于地下的恶劣条件（热、振动、磨蚀性岩石等），并且通常在钻井过程中损坏。 钻头损坏通过国际钻井承包商协会（IADC）开发和发布的行业标准钝分级程序进行量化，然而，该过程主要是手动的，并且非常主观。 这大大降低了数据的有用性，使其不适合大多数钻井优化工作流程，特别是那些寻求使用机器学习算法开发数据驱动模型的工作流程。 使用新发布的iPhone 12 Max上的LIDAR传感器，我们建议评估一种移动的解决方案的可行性，该解决方案使用LIDAR传感器和摄像头，使用手机在钻台上快速构建钻头的三维模型，并自动对钻头进行分级。

To access resources in the subsurface, be it for the recovery of hydrocarbons, the explorations for minerals, or to access geothermal reserves, boreholes must be drilled from the surface. A common class of drill bit used throughout the various industries are drag bits with carbine or steel bodies and inserts made of polycrystalline diamond compact (PDC). These drill bits are often exposed to harsh conditions in the subsurface (heat, vibration, abrasive rock, etc) and are often damaged during the drilling process. Damage to drill bits is quantified through an industry-standard dull grading procedure, developed and published by the International Association of Drilling Contractors (IADC), however, this process is predominantly manual and highly subjective. This significantly reduces the usefulness of the data and makes it unsuitable for most drilling optimization workflows, particularly those seeking to develop data-driven models using machine learning algorithms. Using the LIDAR sensor on the newly released iPhone 12 Max, we propose to evaluate the feasibility of a mobile solution that uses the LIDAR sensor and camera to quickly construct a three-dimensional model of the drill bit on the rig floor using a cell phone and automatically grade the bit.