Penetration-Rate Performance of Roller-Cone Bits

Abstract

Summary The penetration rate obtained with a roller cone bit is controlled by either the cuttings generation process or cuttings removal process. Most previously reported penetration rate models have not previously reported penetration rate models have not explicitly included the cuttings removal effects. This paper presents a penetration rate model that includes the effect of both the initial chip formation and cuttings removal processes. The model is an extension of a previously published model that neglected the effects of cuttings removal. The cuttings removal effects must be included in a valid penetration rate model because they can often penetration rate model because they can often the ROP to less than 20% of the expected ROP for perfect cleaning. perfect cleaning. The model is used to show that the reduction in penetration rate at high borehole pressure is the penetration rate at high borehole pressure is the result of both local cratering effects and global cleaning effects. Increased hydraulics will increase the penetration rate when it is limited by global cleaning effects. The penetration rate reduction due to local cratering effects is largely a function of mud properties and borehole pressure and is not helped much by increases in hydraulics. Introduction Although roller cone bits have been used for over 75 years, the complex mechanics and hydraulics involved with these bits has hindered the complete modeling of the drilling process. The combination of crushing and scraping of the teeth on a rolling cone makes it difficult to model the exact cratering process. The turbulent flow field of the mud under process. The turbulent flow field of the mud under the bit has not been completely modeled, so it is difficult to predict cuttings removal forces. The forces that hold cuttings to the formation can not be predicted very well because of the effects of mud properties on the equalization of the pressure properties on the equalization of the pressure around the chips. Consequently, most penetration rate models are based on empirical matching of experimental data. The complete drilling process is composed of a number of individual actions that must occur in order for the bit to penetrate. The complicated geometry of the bit makes measurement of the individual processes difficult, but test conditions can be designed to identify and model certain basic effects such as cuttings generation, cuttings removal, etc. By developing a model based on both theoretical concepts and experimental data taken under controlled conditions, the complex modeling problem can be reduced to a somewhat simpler one. problem can be reduced to a somewhat simpler one. After a basic model is developed, more complete conditions can be added to further define the model. If the physics of the process are handled property. the addition of the new conditions will not invalidate the previously determined model. The strategy described above was used to develop the model presented in this paper. The discussion of the model is intended mainly as a basis for presenting the effects of various parameters that control the rate of penetration (ROP). The model facilitates the comparison of the relative effects of changing various parameters that may be altered during drilling. It also aids in the evaluation of field bit performance to select conditions that may improve the ROP.

Prediction of Rock Strength using Drilling Data and Sonic Logs

“…The roller cone ROP performed by Amoco research developed the first two term model which linked WOB, RPM, bit size and rock strength [5]. Several ROP models have been developed and modified based on the concept where UCS is inversionally proportional with the rate of penetration.…”

“…A model of the drilling process for tricone bits called perfectcleaning model was derived by Warren and later modified by Hareland and Hoberok which is expressed as [5], [6]:…”

A New Approach for Predrilling the Unconfined Rock Compressive Strength Prediction

“…Then, petrophysical data from over 30 wells will be used for derivation of a UCS profile along the boreholes in different locations of the field. The UCS profile in sections above reservoir is estimated based on Warren's (1987) model using drilling data. The resulting UCS profiles from these 30 wells are then used for derivation of a 3D UCS profile based on neural network modeling in this oilfield.…”

“…Since then, drilling models have advanced and became more specific for different bit types. Warren (1987) proposed a drilling model that later was modified by Hareland by bringing the effect of chip hold-down effect and hole cleaning true.…”

A Model to Predict the Performance of Drilling Operation Using SVM Approach in One of the Iranian Oilfields

“…Thus, the structural properties and reservoir depth are the most influential factors in the rate of rock penetration; in respect of the way, as the depth increases, the formations become harder and the penetration rate decreases. Moreover, due to the depth of the wells in the oil fields of Iran, the assessment of the penetration rate is of importance [8][9][10][11][12][13][14][15].…”