一种新的稳健钻井速度模型

Mohammed Murif Al-Rubaii محمد مريف الربعي, R. Gajbhiye, A. Al-Yami, R. Alouhali
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引用次数: 0

摘要

当涉及到修井和开发井的规划和钻井时,钻井速度仍然是一个主要挑战。钻井工程师的主要任务是设计井,优化时间、成本、经济性和安全性。需要分析以前钻井的作业记录,以执行优化技术,以降低新井的钻井成本。在许多潜在的优化方法中,机械钻速(ROP)对钻井成本效益的影响最为明显,但为了确保最佳的机械钻速,必须对其进行设计。有几种相关性、方法、设计、模型、工具、图表、现场结果和实验研究来提高钻井性能。其中许多方法是有效的,但有些方法不完整,不适合钻井作业,因为它们基于未经证实的理论,缺乏适当的实验数据。适当的模型必须包含影响渗透速度的所有因素,以便为优化井设计提供有意义的工具。这项工作的目的是开发一种优化钻井速度的新方法,该方法将更准确地模拟钻进速度,从而有助于提高钻井效率和成本。首先收集和分析特定井段的钻井参数和泥浆流变特性,确定泥浆特性和钻井参数对ROP性能的影响。所选择的参数和属性均来自相同的井眼尺寸、地层类型和泥浆类型。然后评估泥浆流变特性与ROP之间的关系,以确定其强度。这一步骤有助于确定泥浆流变特性对估计ROP的重要性,从而优化钻井作业并缩短钻井时间。这是第一个将钻井液性质、钻井参数、岩屑体积和狗腿严重程度与钻速优化同时结合在一起的模型。将开发的模型与几个不同油田具有挑战性井段的现场数据进行了比较。结果表明,该方法的相关系数回归值与实际ROP值吻合,准确率较高,达到90%左右。新模型显示了将泥浆特性、岩屑体积百分比、钻井参数和狗腿严重程度结合起来的重要性,因为这将使其适用于任何类型的井眼或井段,例如(垂直、斜井和水平)。开发的模型可以帮助钻井工程师通过有效地优化钻井速度,选择改进的钻井参数、泥浆性质、环空岩屑体积或岩屑浓度的优化值以及狗腿严重程度值。它可用于实时操作中心,参与钻井自动化项目。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A New Robust Drilling Rate Model
Drilling rate remains a major challenge when it comes to planning and drilling workover and development wells. The main mission of a drilling engineer is to design a well optimizing time, cost, economics and safety. Analysis of previously drilled wells operations' records is required to perform optimization techniques to reduce drilling cost for new wells to be drilled. Among the many potential optimizations, Rate of Penetration (ROP) has the most obvious impact on cost effectiveness of a well's drilling, but to ensure optimized rate of penetration, it must be engineered. There are several correlations, methods, designs, models, tools, charts, fields' results, and experimental studies to enhance the well drilling performance. Many of these are effective, but some others are incomplete and not suited for drilling operations as they are based on unproven theory and lack proper experimental data. Proper models must include knowledge of all factors that affect rate of penetration in order to provide a meaningful tool for optimizing the well design. The objective of this work is to develop a new method for optimized drilling rate that will model rate of penetration more accurately and therefore facilitate improving drilling efficiency and cost. The drilling parameters and mud rheological properties in certain hole sections were collected and analyzed first to determine the effect of mud properties and drilling parameters on ROP performance. The parameters and properties that are selected are from the same hole size, formation type and mud type. The relationship between mud rheological properties and ROP was then evaluated to determine how strong it is. This step helps to determine the significance of mud rheological properties on estimating ROP and that will lead to optimization of the drilling operation and reduction in the drilling time. This is the first model combining the drilling fluid properties, drilling parameters, cuttings volume and dogleg severity with rate of penetration optimization simultaneously. The developed model has been compared with using field data during drilling challenging hole sections in several different fields. It has shown high correlation coefficient regression value matching with actual ROP Values with high percentage of accuracy, which is about 90 %. The new model showed the importance of combining mud properties, cuttings volume percent, drilling parameters and dogleg severity since that will make it applicable in any type of wellbore or hole section such as (vertical, deviated and horizontal). The developed model can assist drilling engineers in selecting improved drilling parameters, mud properties, optimized value of cuttings volume or cuttings concentrations in annulus and dogleg severity value by optimizing the drilling rate using the developed model effectively. It can be used in real time operating center to participate for drilling Automation projects.
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