Real-Time Drill Bit Wear Prediction by Combining Rock Energy and Drilling Strength Concepts

Abstract

A central element to reduce drilling cost is to improve drilling operation by analyzing real-time data. Developing advanced real-time analysis tools is one way to improve the drilling operation. Two approaches which currently are used for optimizing the actual rotary drilling process are mechanical specific energy and inverted rate of penetration models. The mechanical specific energy method is defined as the work needed to destroy a given volume of the rock. It can act as a tool during the drilling operation to detect changes in drilling efficiency thus providing a method to optimize the drilling parameters to enhance instatanious rate of penetration. Rate of penetration models, on the other hand, can be used to calculate formation drillability considering the effects of drilling parameters, bits design and bit wear. Drilling optimization using rate of penetration models is done by changing the drilling parameters and/or bit design to find the optimum drilling scenario for an entire bit run. The mechanical specific energy log and the drillability ratio differ when mud weight is changed and when bits are worn. These two differences are due the fact that mechanical specific energy does not include bit wear as well as the effect of changing mud weight. By combining these methods and modifying the mechanical specific energy equations to incorporate these effects and the mechanical specific energy can be used as a real-time trending tool for bit wear estimations. In this analysis, wells from offshore Middle East and onshore North America are analyzed. The field results are very encouraging in that the bit wear for both roller cone and PDC bits can be predicted. The field validation of this new approach shows that the supplementary information on the bit wear status can in some cases benefit in the decision of when to pull the bit while it still is in the hole and thereby possibly improve overall economics of the drilling operation. Introduction For any given drilling operation, several drilling technologies are available to optimize the process drilling. The intent of any drilling optimization process is to conduct the drilling operation in a safely and in the most cost-effective manner possible. One important aspect of this optimization scheme is to asses drilling performance continuously during the drilling operation. The operators drill rate management process should be designed to maximize the overall rate of penetration based on the cumulative footage drilled. The manner in which different drilling parameters can affect penetration rate is complex. However, two main methods of optimizing drilling are mechanical specific energy (MSE) and inverted rate of penetration (ROP) models. Both methods can help to optimize the drilling operation by analyzing drilling variables like weight on bit and rotary speed. One effective way of drilling a well would be to have a rough idea of the ‘in hole’ bit wear status. The goal of this paper is to establish a method for evaluating real time bit wear and to create a field tool that can assist in the decision when to pull the bit. Rate of Penetration (ROP) Several ROP models have been proposed to combine known experiemental or mathematically derived relationships between operating conditions and rate of penetration. These models make it possible to apply formal optimization methods to the problem of selecting the best weight on bit and rotary speed to achieve the minimum cost per foot. By utilizing ROP models significant drilling cost reductions and increase in rate of penetration has been reported (Nygaard, et al. 2002, Hareland et al. 2007).

New Approach in Real-Time Bit Wear Prediction

“…This will be done using a combination of the ROP models and rock Mechanical Specific Energy. By assuming no bit wear initially and calculating the CCS using the ROP models, it can then be used in conjunction with MSE to calculate the fractional bit wear while drilling (2) as shown below: This approach will give us a new method and tool for predicting real -time bit wear which will help optimize drilling operation in real-time while drilling. It can also be integrated as a module in drilling optimization software after it has been developed, verified and tested.…”

“…Bit wear is one of the main causes that affect drilling performance. This work aims to employ more comprehensive ROP models combined with the MSE model through a developed methodology to predict bit wear especially in real time while drilling (2) . A previous methodology was established based on using Burgoyne and Young ROP model for both rollercone and PDC bits which shows uncertainties for the calculated results.…”

Development of an Intelligent System for the Analysis of both Static and Real-time Oil and Gas Well Drilling Data

“…The system uses a newly developed real-time bit wear model (Rashidi et al, 2008) which is a combination method of the rock energy (Mechanical Specific Energy, MSE) model and formation drillbility from the rate of penetration (ROP) model. The ROP and MSE models are competitively using in oil industry to analyze drilling performance and perform a continuous drill-off test respectively.…”

“…The formation drillability, f 1 is obtained from equation 2. The new real-time bit wear model proposed by (Rashidi et al, 2008), is developed based on equations (1) and (2) and the fractional bit wear can be estimated from the following equations when the bit is in hole:…”

A New Approach for Predrilling the Unconfined Rock Compressive Strength Prediction

“…Rashidi et al (2008) have shown that uniaxial compression tests are influenced by several factors, such as the size and shape of the test sample, rate of loading, amount and type of fluid present in the rock sample, mineralogy, grain size, grain shape, grain sorting, and rate of loading. In addition to weathering, rock structure alteration due to diffusion of incompatible fluids and inaccurate handling of the cores in conjunction with stress unloading causes differences between measured rock strength from reality (Nabaei et al, 2010).…”