Patent Publication Number: US-10781682-B2

Title: Systems and methods for optimizing rate of penetration in drilling operations

Description:
BACKGROUND 
     1. Field 
     This disclosure relates generally to the field of construction of wellbores through subsurface formations. More particularly the disclosure relates to methods for automatically calculating and displaying to drilling operations personnel values of drilling operating parameters that may optimize drilling of such wellbores and to characterize drilling performance on a specific wellbore with respect to benchmarks for such performance. 
     2. Description of Related Art 
     Background 
     Drilling wellbores through subsurface formations includes suspending a “string” of drill pipe (“drill string”) from a drilling unit or similar lifting apparatus and operating a set of drilling tools and rotating a drill bit disposed at the bottom end of the drill string. The drill bit may be rotated by rotating the entire drill string from the surface and/or by operating a motor disposed in the set of drilling tools. The motor may be, for example, operated by the flow of drilling fluid (“mud”) through an interior passage in the drill string. The mud leaves the drill string through the drill bit and returns to the surface through an annular space between the drilled wellbore wall and the exterior of the drill string. The returning mud cools and lubricates the drill bit, lifts drill cuttings to the surface and provides hydrostatic pressure to mechanically stabilize the wellbore and prevent fluid under pressure from entering the wellbore from certain permeable formations exposed to the wellbore. The mud may also include materials to create an impermeable barrier (“filter cake”) on exposed formations having a lower fluid pressure than the hydrostatic pressure of the mud in the annular space so that mud will not flow into such formations in any substantial amount. 
     The drilling unit may have controls for selecting “drilling operating parameters.” In the present context, the term drilling operating parameters means those parameters which are controllable by the drilling unit operator and/or associated personnel and include, as non-limiting examples, axial force (weight) of the drill string suspended by the drilling unit as applied to the drill bit, rotational speed of the drill bit (“RPM”), the rate at which drilling fluid is pumped into the drill string, and the rotational orientation or tool face (“TF”) of the drill string when certain types of motors are used to rotate the drill bit. As a result of the particular values of drilling operating parameters such as the foregoing, the results may include that wellbore will be drilled (lengthened) at a particular rate and along a trajectory (well path) and may result in a particular measured pressure of the drilling fluid at the point of entry into the drill string or proximate thereto, called standpipe pressure (“SPP”). The foregoing are non-limiting examples of “drilling response parameters.” 
     Stuck pipe while drilling can be a common problem in the oil industry. In fact, stuck pipe has become a more significant source of non-productive time because extended reach horizontal drilling has gained use in unconventional shale plays. Unfortunately, stuck pipe is often difficult to detect until after the sticking event has already occurred. 
     Typically, drilling jars, which are intended to create a hammer effect on the drill string, are run to provide a way to “un-stick” the drill string. Yet, extended reach horizontal drilling has changed traditional thinking because it reduces the effectiveness of jars by limiting force transfer from the vertical section to the horizontal section of the well. For this reason, many operators have stopped running drilling jars in these types of wells. Consequently, operators have very few ways to detect/prevent stuck pipe so that in some sense nothing can be done to address the issue if it occurs. 
     Other than using drilling jars, many operators mandate pumping high viscosity “sweeps” at some regular interval while drilling. A typical frequency involves one sweep for every three stands of pipe drilled. The “sweeps” are meant to clean the borehole near the bit and reduce the changes of sticking. 
     Operators also rely on the expertise of rig site supervisors to be able to detect when the well is being drilled “too fast” and/or if any of the telltale signs of impending stuck pipe are being observed at the surface. Operators may also supplement these efforts by having a remote tactical operations center (RTOC) monitor drilling operations remotely. 
     Historically, raw real-time data may be plotted during drilling. To determine an appropriate rate of penetration, operators rely on human interpretation of whether the pump pressure, torque, hook load, and other parameters fall outside of the “normal” or “acceptable” ranges. Changes to rate of penetration (ROP) in what is sometimes called “controlled drilling” can be made based on human judgment. For example, limits can be placed on ROP based on experience in the area (i.e. operators may merely know how fast drilling was proceeding when the last problem occurred). Additionally, limits can be placed on ROP based on the ability of surface equipment to simply clean out solids from the mud coming through the flow line. 
     As will be appreciated, the above methods are highly subjective and may be unreliable. In many instance, a drilling regime used at one well is simply just copied to the next well without regard to changes in geology, drilling conditions, etc. In short, current techniques to mitigate stuck pipe during drilling are insufficient. 
     What is needed is a real-time system to proactively calculate a desired rate-of-penetration (ROP) during a drilling operation to mitigate issues with stuck pipe. The subject matter of the present disclosure is directed to overcoming, or at least reducing the effects of, one or more of the problems set forth above. 
     SUMMARY 
     Systems and methods for providing efficient hole cleaning in vertical, deviated and horizontal holes by developing an effective hole cleaning model by utilizing carrying capacity index (CCI) and cutting concentration in annulus (CCA), and integrating the hole cleaning model that links hole cleaning and drilling rate by using drilling specific energy (DSE) to optimize performance are disclosed. More specifically, the systems and methods ensure optimum mud rheology values that have effective influence on drilling mud from the aspects of equivalent circulating density (ECD), cuttings transport, shear thinning, and thixotropic properties. 
     One example embodiment is a method of drilling a borehole with a drill tool of a drilling system that uses drilling mud to transport cuttings of a formation to surface. The method includes receiving a plurality of input parameters of a drilling operation conducted with the drilling system, the input parameters at least including a cuttings parameter related to the cuttings produced in the drilling operation, determining a current concentration of the cuttings in the drilling operation at least near the drill tool based on the obtained parameters, determining a desired rate of penetration for the drilling operation based on the determined concentration, and altering a current rate of penetration based on the determined rate. 
     Another example embodiment is a program storage device having program instructions stored thereon for causing a programmable control device to perform a method of drilling a borehole according to the above method. 
     Another example embodiment is a drilling system for drilling a borehole with a drill tool using drilling mud to transport cuttings of a formation to surface. The system includes storage storing historical information, an interface obtaining a plurality of parameters of a drilling operation conducted with the drilling system, the input parameters at least including a cuttings parameter related to the cuttings produced in the drilling operation, and a processing unit in communication with the storage and the interface and configured to receive a plurality of input parameters of a drilling operation conducted with the drilling system, the input parameters at least including a cuttings parameter related to the cuttings produced in the drilling operation, determine a current concentration of the cuttings in the drilling operation at least near the drill tool based on the obtained parameters, determine a desired rate of penetration for the drilling operation based on the determined concentration, and alter a current rate of penetration based on the determined rate. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
       The foregoing aspects, features, and advantages of embodiments of the present disclosure will further be appreciated when considered with reference to the following description of embodiments and accompanying drawings. In describing embodiments of the disclosure illustrated in the appended drawings, specific terminology will be used for the sake of clarity. However, the disclosure is not intended to be limited to the specific terms used, and it is to be understood that each specific term includes equivalents that operate in a similar manner to accomplish a similar purpose. 
       For simplicity and clarity of illustration, the drawing figures illustrate the general manner of construction, and descriptions and details of well-known features and techniques may be omitted to avoid unnecessarily obscuring the discussion of the described embodiments of the invention. Additionally, elements in the drawing figures are not necessarily drawn to scale. For example, the dimensions of some of the elements in the figures may be exaggerated relative to other elements to help improve understanding of embodiments of the present invention. Like reference numerals refer to like elements throughout the specification. 
         FIG. 1  is a schematic of a drilling and measurement system including a bottom hole assembly and a logging and control system, according to one or more example embodiments. 
         FIG. 2  is a detailed view of the logging and control system illustrated in  FIG. 1 , according to one or more example embodiments. 
         FIG. 3  is a block diagram illustrating a method for optimizing rate of penetration in a drilling operation, according to one or more example embodiments. 
         FIG. 4  is a flow diagram illustrating example steps in a method for optimizing rate of penetration in a drilling operation, according to one or more example embodiments. 
         FIG. 5  is a flow diagram illustrating example steps in a method for optimizing rate of penetration in a drilling operation, according to one or more example embodiments. 
         FIG. 6  is a table showing test results obtained using a method for optimizing rate of penetration in a drilling operation, according to one or more example embodiments. 
         FIG. 7  is a table showing test results obtained via model trials performed in two wells using a method for optimizing rate of penetration in a drilling operation, according to one or more example embodiments. 
         FIG. 8A  is a graph plotting depth in feet versus rate of penetration in feet per hour prior to applying an optimization model, according to one or more example embodiments. 
         FIG. 8B  is a graph plotting depth in feet versus rate of penetration in feet per hour after applying an optimization model, according to one or more example embodiments. 
         FIG. 9A  is a graph plotting actual rate of penetration in feet per hour versus measured rate of penetration in feet per hour prior to applying an optimization model, according to one or more example embodiments. 
         FIG. 9B  is a graph plotting actual rate of penetration in feet per hour versus measured rate of penetration in feet per hour after applying an optimization model, according to one or more example embodiments. 
         FIG. 10A  is a line graph plotting depth in feet versus actual rate of penetration in feet per hour and measured rate of penetration in feet per hour prior to applying an optimization model, according to one or more example embodiments. 
         FIG. 10B  is a line graph plotting depth in feet versus actual rate of penetration in feet per hour and measured rate of penetration in feet per hour after applying an optimization model, according to one or more example embodiments. 
     
    
    
     DETAILED DESCRIPTION 
     The methods and systems of the present disclosure will now be described more fully hereinafter with reference to the accompanying drawings in which embodiments are shown. The methods and systems of the present disclosure may be in many different forms and should not be construed as limited to the illustrated embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey its scope to those skilled in the art. 
       FIG. 1  shows a simplified view of an example drilling and measurement system that may be used in some embodiments. The drilling and measurement system shown in  FIG. 1  may be deployed for drilling either onshore or offshore wellbores. In a drilling and measurement system as shown in  FIG. 1 , a wellbore  111  may be formed in subsurface formations by rotary drilling in a manner that is well known to those skilled in the art. Although the wellbore  111  in  FIG. 1  is shown as being drilled substantially straight and vertically, some embodiments may be directionally drilled, i.e. along a selected trajectory in the subsurface. 
     A drill string  112  is suspended within the wellbore  111  and has a bottom hole assembly (BHA)  151  which includes a drill bit  155  at its lower (distal) end. The surface portion of the drilling and measurement system includes a platform and derrick assembly  153  positioned over the wellbore  111 . The platform and derrick assembly  153  may include a rotary table  116 , kelly  117 , hook  118  and rotary swivel  119  to suspend, axially move and rotate the drill string  112 . In a drilling operation, the drill string  112  may be rotated by the rotary table  116  (energized by means not shown), which engages the kelly  117  at the upper end of the drill string  112 . Rotational speed of the rotary table  116  and corresponding rotational speed of the drill string  112  may be measured un a rotational speed sensor  116 A, which may be in signal communication with a computer in a surface logging, recording and control system  152  (explained further below). The drill string  112  may be suspended in the wellbore  111  from a hook  118 , attached to a traveling block (also not shown), through the kelly  117  and a rotary swivel  119  which permits rotation of the drill string  112  relative to the hook  118  when the rotary table  116  is operates. As is well known, a top drive system (not shown) may be used in other embodiments instead of the rotary table  116 , kelly  117  and swivel rotary  119 . 
     Drilling fluid (“mud”)  126  may be stored in a tank or pit  127  disposed at the well site. A pump  129  moves the drilling fluid  126  to from the tank or pit  127  under pressure to the interior of the drill string  112  via a port in the swivel  119 , which causes the drilling fluid  126  to flow downwardly through the drill string  112 , as indicated by the directional arrow  158 . The drilling fluid  126  travels through the interior of the drill string  112  and exits the drill string  112  via ports in the drill bit  155 , and then circulates upwardly through the annulus region between the outside of the drill string  112  and the wall of the borehole, as indicated by the directional arrows  159 . In this known manner, the drilling fluid lubricates the drill bit  155  and carries formation cuttings created by the drill bit  155  up to the surface as the drilling fluid  126  is returned to the pit  127  for cleaning and recirculation. Pressure of the drilling fluid as it leaves the pump  129  may be measured by a pressure sensor  158  in pressure communication with the discharge side of the pump  129  (at any position along the connection between the pump  129  discharge and the upper end of the drill string  112 ). The pressure sensor  158  may be in signal communication with a computer forming part of the surface logging, recording and control system  152 , to be explained further below. 
     The drill string  112  typically includes a BHA  151  proximate its distal end. In the present example embodiment, the BHA  151  is shown as having a measurement while drilling (MWD) module  130  and one or more logging while drilling (LWD) modules  120  (with reference number  120 A depicting a second LWD module  120 ). As used herein, the term “module” as applied to MWD and LWD devices is understood to mean either a single instrument or a suite of multiple instruments contained in a single modular device. In some embodiments, the BHA  151  may include a “steerable” hydraulically operated drilling motor of types well known in the art, shown at  150 , and the drill bit  155  at the distal end. 
     The LWD modules  120  may be housed in one or more drill collars and may include one or more types of well logging instruments. The LWD modules  120  may include capabilities for measuring, processing, and storing information, as well as for communicating with the surface equipment. By way of example, the LWD module  120  may include, without limitation one of a nuclear magnetic resonance (NMR) well logging tool, a nuclear well logging tool, a resistivity well logging tool, an acoustic well logging tool, or a dielectric well logging tool, and so forth, and may include capabilities for measuring, processing, and storing information, and for communicating with surface equipment, e.g., the surface logging, recording and control unit  152 . 
     The MWD module  130  may also be housed in a drill collar, and may contain one or more devices for measuring characteristics of the drill string  112  and drill bit  155 . In the present embodiment, the MWD module  130  may include one or more of the following types of measuring devices: a weight-on-bit (axial load) sensor, a torque sensor, a vibration sensor, a shock sensor, a stick/slip sensor, a direction measuring device, and an inclination and geomagnetic or geodetic direction sensor set (the latter sometimes being referred to collectively as a “D&amp;I package”). The MWD module  130  may further include an apparatus (not shown) for generating electrical power for the downhole system. For example, electrical power generated by the MWD module  130  may be used to supply power to the MWD module  130  and the LWD module(s)  120 . In some embodiments, the foregoing apparatus (not shown) may include a turbine-operated generator or alternator powered by the flow of the drilling fluid  126 . It is understood, however, that other electrical power and/or battery systems may be used to supply power to the MWD and/or LWD modules. 
     In the present example embodiment, the drilling and measurement system may include a torque sensor  159  proximate the surface. The torque sensor  159  may be implemented, for example in a sub  160  disposed proximate the top of the drill string  112 , and may communicate wirelessly to a computer in the surface logging, recording and control system  152 , explained further below. In other embodiments, the torque sensor  159  may be implemented as a current sensor coupled to an electric motor (not shown) used to drive the rotary table  116 . In the present example embodiment, an axial load (weight) on the hook  118  may be measured by a hookload sensor  157 , which may be implemented, for example, as a strain gauge. The sub  160  may also include a hook elevation sensor  161  for determining the elevation of the hook  118  at any moment in time. The hook elevation sensor  161  may be implemented, for example as an acoustic or laser distance measuring sensor. Measurements of hook elevation with respect to time may be used to determine a rate of axial movement of the drill string  112 . The hook elevation sensor may also be implemented as a rotary encoder coupled to a winch drum used to extend and retract a drill line used to raise and lower the hook (not shown in the Figure for clarity). Uses of such rate of movement, rotational speed of the rotary table  116  (or, correspondingly the drill string  112 ), torque and axial loading (weight) made at the surface and/or in the MWD module  130  may be used in one more computers as will be explained further below. 
     The operation of the MWD and LWD instruments of  FIG. 1  may be controlled by, and sensor measurements from the various sensors in the MWD and LWD modules and the other sensors disposed on the drilling and measurement unit described above may be recorded and analyzed using the surface logging, recording and control system  152 . The surface logging, recording and control system  152  may include one or more processor-based computing systems or computers. In the present context, a processor may include a microprocessor, programmable logic devices (PLDs), field-gate programmable arrays (FPGAs), application-specific integrated circuits (ASICs), system-on-a-chip processors (SoCs), or any other suitable integrated circuit capable of executing encoded instructions stored, for example, on tangible computer-readable media (e.g., read-only memory, random access memory, a hard drive, optical disk, flash memory, etc.). Such instructions may correspond to, for instance, workflows and the like for carrying out a drilling operation, algorithms and routines for processing data received at the surface from the BHA  155  (e.g., as part of an inversion to obtain one or more desired formation parameters), and from the other sensors described above associated with the drilling and measurement system. The surface logging, recording and control system  152  may include one or more computer systems as will be explained with reference to  FIG. 2 . The other previously described sensors including the torque sensor  159 , the pressure sensor  158 , the hookload sensor  157  and the hook elevation sensor  161  may all be in signal communication, e.g., wirelessly or by electrical cable with the surface logging, recording and control system  152 . Measurements from the foregoing sensors and some of the sensors in the MWD and LWD modules may be used in various embodiments to be further explained below. 
     The control system  152  is schematically shown in  FIG. 2 . As briefly depicted, the control system  152  includes a processing unit  102 , which can be part of a computer system, a server, a programmable logic controller, etc. The processing unit  102  has a number of monitors or controls  103   a - b  used for monitoring or control during drilling operations. As shown herein, the processing unit  102  operates a monitor  103   a  for weight-on-bit, a monitor  103   b  for flow, and a monitor  103   c  for ROP to name a few. 
     Using input/output interfaces  104 , the processing unit  102  can communicate with various components of the drilling system shown in  FIG. 1  to obtain information on parameters and to communicate with various sensors, actuators, and logic control for the various system components as the case may be. In terms of the current controls discussed, signals communicated to the drilling system&#39;s components can be related to controls for altering the rate of penetration of the drilling system in the drilling operation. The signals can include, but are not limited to, signals to control the flow rate, weight on bit, hookload, RPM, rotary torque, etc. 
     The processing unit  102  also communicatively couples to a database or storage  106  having historical data  108 , correlation information  109 , and other stored information. The historical data  108  characterizes the cuttings concentrations, ROP, etc. with stuck pipe incidents based on previous drilling operations. The correlation information  109  is compiled from the historical data based on the analysis disclosed herein and can be organized and characterized based on borehole types, borehole depths, drilling fluids, operating conditions, and other scenarios and arrangements. 
     Before going into further details of the drilling system, the control system  152 , and the drilling process, discussion first turns to how a maximum “safe” rate of penetration is determined based on a concentration of cuttings at or near the bottom hole assembly  151  (e.g., drill tool or bit  155 ). In terms of the present disclosure, the concentration of cuttings can be determined at the drill bit or at least near the drill bit (i.e., around the area of the bottom hole assembly  151  having the drill bit  155 ). As is customary, the bottom hole assembly  151  of a drilling system typically has a drill tool or bit  155  and can have a number of other components, such as stabilizers, drill collars, measurement while drilling (MWD) instruments, rotary steerable tool, and the like. The overall size and length of the bottom hole assembly depends on a number of factors, such as desired weight on bit, weight of the drill collar, mud weight, buoyancy, etc. 
     Based on a mass balance for cuttings entering the flow stream and the ability to remove them, the control system  152  can calculate a cuttings concentration at the bit face and the near-bit area at any given time for both historical and real-time data. This is termed cuttings concentration f c . In particular, the control system  152  stores information that is based on historical data sets and that correlates calculated cuttings concentration f c  versus depth for on-bottom drilling where problems such as stuck pipe occurred. The stored information establishes an empirical “safe” or “acceptable” cuttings concentration f c  for drilling under various drilling parameters. The “safe” cuttings concentration f c  may vary based on the inclination of the borehole, type of BHA, formation properties or type (e.g. shale, limestone, etc.), mud weight, current drilling operation (connection, pump sweep, rotary drilling, etc.) and other factors. 
     The control system  152  obtains relevant drilling data in real-time while drilling from an available data stream, such as available in Wellsite Information Transfer Specification (WITS) or Wellsite Information Transfer Standard Markup Language (WITSML) data streams. The relevant drilling data can be supplemented with various user inputs, such as mud weight and the like. The control system  152  may also use log data. 
     Using the stored information and the real-time data, the control system  152  can calculate a “safe” or “acceptable” cuttings concentration f c  for drilling, which in turn can provide a maximum “safe” ROP at any given time or depth. Equations used by the control system  152  for calculating the “safe” cuttings concentration f c  and maximum “safe” ROP for drilling will now be discussed. 
       FIG. 3  is a block diagram illustrating a method  300  for optimizing rate of penetration in a drilling operation, according to one or more example embodiments. As illustrated in this block diagram, the system receives input data  302  and performs preliminary calculations  304 . Based on the preliminary calculations  304 , the system performs model calculations  306  to make decisions and control the drilling operations. The input data  302  may include one or more input parameters including, for example, hole size, mud type, footage, hours spent for drilling the footage, mud density in pounds per cubic feet (pcf) and pounds per gallon (ppg), funnel viscosity, plastic viscosity (PV) in centipoise (cp), yield point (YP) in lb/100 sqft, weight of blend (WOB) in Klb, revolutions per minute (RPM), stand pipe pressure in psi, torque in lbf·ft, total flow area of the bit in square inches, initial gel and final gel types, and flow rate of the mud pump. Before using the hole cleaning models, however, a plurality of output parameters are determined by the system using the input parameters provided in the input data  302 . These output parameters include rate of penetration (ROP), consistency index (K), fluid behavior index (n), Φ 600  and Φ 300 , apparent and effective viscosities, cutting diameter (i.e. ROP/RPM), annular velocity (V ann ), critical velocity (V c ), cutting rise velocity (V cr ), cutting slip velocity (V s ), consistency index to the power n (K n ), velocity of nozzles, pressure drop at the drilling bit, hydraulic horsepower (HHP), hydraulic horse power per square inch (HSI), jet impact force (F j ), transport ration (TR), V cr /V ann  ratio and dc/OH ratio, PV/YP, YP/PV, G i /G f , G f /G i , K (1-(dc/OH){circumflex over ( )}n) , modified carrying capacity index (MCCI), and drilling specific energy (DSE). After the plurality of output parameters are calculated, the system may perform model calculations  306  for decision making. More specifically, the system may use one of three or more methods to determine the cutting concentration in the annulus (CCA). The methods may include Newitt&#39;s method where the system determines that if the CCA is greater than 0.05, then it is considered poor hole cleaning. Else, the system may consider it good hole cleaning and have room to optimize till the CCA value equals 0.05. The next method is API method, where if the system determines that the CCA is greater than 0.05, then it is considered bad hole cleaning. Else, the system may consider it a good hole cleaning and have room to optimize till the CCA value equals 0.05. The next method is carrying capacity index (CCI) method, where if the system determines that the CCI is less than 0.5, then it is considered a bad hole cleaning. Else, the system may consider it a good hole cleaning and have room for optimizing till the CCI value equals 0.5. 
     Cutting concentration in the annulus is an effective tool that can indicate what percentage of cuttings generated while drilling are loaded in the annulus. The cutting concentration in annulus has a limit that is not supposed to be exceeded. For example, in some instances the limit of the CCA is within the range of 5% to 8%. If the CCA exceeds this limit, it can strongly lead to severe hole problems. There are several logical reasons that can explain why exceeding the limit can induce hole problems. CCA can help in optimizing the rate of penetration since the limit is known and recognized. The input parameters to determining CCA are rate of penetration (ROP), hole size (OH), flow rate of mud pump (GPM), and transport ratio (TR). CCA can be calculated using the following formula: 
     
       
         
           
             
               C 
               ⁢ 
               
                   
               
               ⁢ 
               C 
               ⁢ 
               
                   
               
               ⁢ 
               A 
             
             = 
             
               
                 R 
                 ⁢ 
                 
                     
                 
                 ⁢ 
                 O 
                 ⁢ 
                 
                     
                 
                 ⁢ 
                 P 
                 ⁢ 
                 
                     
                 
                 ⁢ 
                 
                   OH 
                   2 
                 
               
               
                 1472 
                 ⁢ 
                 
                     
                 
                 ⁢ 
                 G 
                 ⁢ 
                 
                     
                 
                 ⁢ 
                 P 
                 ⁢ 
                 
                     
                 
                 ⁢ 
                 M 
                 ⁢ 
                 
                     
                 
                 ⁢ 
                 T 
                 ⁢ 
                 
                     
                 
                 ⁢ 
                 R 
               
             
           
         
       
     
     In some cases, the size of cuttings, size of annulus, flow pattern, and down hole fluid properties cannot be determined with high degree of accuracy. CCI is a simple empirical index to help predict hole cleaning. The product of the three most important and influential variables on the transport ratio (TR) is equal to a value around 400,000 where cuttings are properly lifted to the surface. Good hole cleaning is indicated when the cuttings have sharp shape edges. Round edges indicate that there is tumbling action in the annulus because cuttings are not transported to surface quickly. The hole cleaning index or ratio is expected to be 1 or greater than 1 for good hole cleaning condition. When a CCI value is 0.5 or less, the cuttings are more rounded and small due to inefficient hole cleaning (longer residence time in annulus). Good hole cleaning can be achieved by increasing the value of K (consistency index) and annular velocity. This CCI is applicable in vertical hole sections of inclination from 0 to 25 degrees. For deviated and horizontal hole section, CCI must be modified. Modified CCI is applicable for inclination greater than 25 degrees. In a vertical well, the formula for determining CCI may be given as follows: 
     MW=the mud weight in PPG, 
     A v =Mud annular Velocity; ft/min 
     K=the consistency index, equivalent cp 
     K=511 (1-n)  (PV+YP), 
     PV=Plastic viscosity; cp 
     YP=yield point (lb/100 ft 2 ) 
     n=3.32 log ((2PV+YP)/(PV+YP)) 
     
       
         
           
             CCI 
             = 
             
               
                 MW 
                 ⁢ 
                 
                     
                 
                 ⁢ 
                 K 
                 ⁢ 
                 
                   
                       
                   
                   ⁢ 
                   
                       
                   
                 
                 ⁢ 
                 Av 
               
               
                 400 
                 , 
                 000 
               
             
           
         
       
     
     For a horizontal well, the angle factor (Af) comes into play, and CCI can be determined using the following formula: 
     
       
         
           
             CCI 
             = 
             
               ( 
               
                 
                   K 
                   ⁢ 
                   
                       
                   
                   ⁢ 
                   SG 
                   ⁢ 
                   
                       
                   
                   ⁢ 
                   Af 
                 
                 
                   3585 
                   ⁢ 
                   
                       
                   
                   ⁢ 
                   Aa 
                 
               
               ) 
             
           
         
       
     
     K: consistency index, equivalent cp 
     K=511 (1-n)  (PV+YP), 
     PV: Plastic viscosity; 
     YP: Yield point (lb/100 ft 2 ) 
     n=3.32 log((2PV+YP)/(PV+YP)) 
     A a : Annular Area; ft 2 . 
     SG: Specific gravity. 
     CCA indicates the amount of cuttings generated by the measured ROP using sensor measurement so that one can make sure the amount of cuttings is smooth with measured ROP to enable one to know the target ROP that can be achieved without affecting the hole cleaning&#39;s smoothness. CCI ensures the perfect mud properties that will empower the drilling fluid capacity to transport the generated drilling cuttings. Hence one can ensure the generated drilling cuttings are smooth with measured ROP and one can optimize it to targeted ROP. 
     Mechanical and drilling specific energy (MSE and DSE) generally indicate how efficient the drilling operation is. Specifically, DSE is the energy needed for removing a unit volume of rock. To obtain excellent performance of drilling, mechanical specific energy is decreased in order to have optimum drilling rate. To minimize MSE or DSE the drilling parameters such as WOB, Torque, ROP and RPM must be controlled. MSE is a ratio, and demonstrates the relationship among the required energy to destroy the rock and rate of penetration. The ratio is constant for a given rock. DSE or MSE is utilized to elect the required WOB and RPM that can increase the drilling rate till the point that ROP starts to deviate from linearity to flounder point and that indicate more hole cleaning efficiency is required to be achieved. The input parameters for determining DSE are WOB, RPM, Torque, ROP, Bit diameters or hole size and hydraulic horsepower of bit (HHP). DSE or MSE can be measured by the sensor of the rig or calculated using the following formula: 
     
       
         
           
             DSE 
             = 
             
               
                 
                   4 
                   ⁢ 
                   
                       
                   
                   ⁢ 
                   WOB 
                 
                 
                   nD 
                   B 
                   2 
                 
               
               + 
               
                 
                   480 
                   ⁢ 
                   
                       
                   
                   ⁢ 
                   RPM 
                   ⁢ 
                   
                       
                   
                   ⁢ 
                   TRQ 
                 
                 
                   
                     D 
                     B 
                     2 
                   
                   ⁢ 
                   
                       
                   
                   ⁢ 
                   ROP 
                 
               
               - 
               
                 
                   3 
                   , 
                   189 
                   , 
                   335 
                   ⁢ 
                   
                       
                   
                   ⁢ 
                   
                     HHP 
                     B 
                   
                 
                 
                   
                     D 
                     B 
                     * 
                   
                   ⁢ 
                   
                       
                   
                   ⁢ 
                   ROP 
                 
               
             
           
         
       
     
     The ratio of cuttings or slip velocity to annular velocity is called the transport ratio (TR) and it can be used to describe hole cleaning efficiency. Anything that increases the transport ratio, will increase hole cleaning efficiency in vertical and directional wells. A reduction in slip velocity is one way that the transport ratio can be increased. The slip velocity is influenced by the size, density and shape of drilling cuttings, and rheology, density and velocity of mud. 
     The larger and heavier the cutting, and the lighter and less viscous the fluid, the faster the cutting will slip through the mud. Much of work and studies done in vertical wells were to improve hole cleaning efficiency and is aimed to reduce the slip velocity or increasing the annular velocity. Some initiatives have proposed equations to estimate slip velocity while drilling operations. However, these equations are needed to give precise values in such a complex flow behavior. Optimum flow rate and drilling fluid parameters have important effect on the hole cleaning since generated drilling cuttings can be removed by applying critical velocity and critical flow rate as well. The annular velocity which allows fluid in annuli loaded with cuttings to travel up to the surface is a very critical hole cleaning key. As a rule of thumb of some drilling fluid engineers, the annular velocity of drilling mud should be 1.2 times more than the settling velocity to ensure minimum cuttings movement in annulus. The size, shape, and weight of generated drilling cuttings lead to controlling its rate of slipping through circulating drilling fluid. Low rate of shear of viscosity can significantly affect the capability of carrying of mud in the well bore. Drilling mud must have adequate capability of carrying to transport generated drilling cuttings from the wellbore. 
     Hole cleaning ratio (HCR) is the ratio of the height of annular space above the cuttings beds to the critical height of the cuttings bed. if the height of free region above the cuttings bed is greater than the critical bed height, the more pulling through of cuttings bed without circulating. If ratio is greater than one, there will be no problem. If the ratio is less than one then, problems will be expected. From a study of 50 larger diameter directional wells in North Sea, when the HCR was greater than 1.1, no stuck pipe incidents occurred. When the HCR was less than 0.5, stuck pipe always occurred. As the HCR decreases, the tendency to become stuck increases. As bed height increases, the annular space above the cuttings bed decreases. The larger the BHA (Bottom Hole Assembly), the smaller the cuttings bed must be to pull through it. In general, over pull tend will increase as the BHA diameter increases. The drill string, bit and stabilizer selection should take these factors into account. 
     The effect of the mud weight (MW) is combined together with the rheology factor (RF) and angle factor (Af) to form a single parameter called the Transport Index (TI). Transport index must be greater than one. The larger transport index, the more the hole cleaning efficiency. It indicates the minimum flow rate required for each section even if the washout has been induced. Where MW is in SG (specific gravity) or g/cc. High inclination of hole section means low value of the angle factor value, hence, the difficulty of hole cleaning will be more. The rheology factor (RF) has been found by using PV &amp; YP and the relationship between RF and PV &amp; YP indicates effective hole cleaning. 
       FIG. 4  is a flow diagram illustrating example steps in a further method  400  for optimizing rate of penetration in a drilling operation, according to one or more example embodiments. In this method, the system, for example, receives input data in step  402 , performs calculations in step  404 , and makes decisions in step  406 . The input data may include, among other things, drilling mud properties and well configurations as those listed in  FIG. 3 , for example. The calculations may include, among other things, determining the cutting concentration in annulus (CCA) and carrying capacity index (CCI). The decision making is similar to that shown in  FIG. 3 , where if the CCA is greater than 5% or CCI is less than 0.5, then it is considered a bad hole cleaning, and if the CCA is less than 5% or CCI is greater than 0.5, then it is considered a good hole cleaning. 
       FIG. 5  is a flow diagram illustrating example steps in a further method  500  for optimizing rate of penetration in a drilling operation, according to one or more example embodiments. In this method, the system receives field data in step  502 . The field data may include input data, such as that shown in  FIG. 3 , for example. Upon receiving the field data, the system initially determines values for CCA and CCI. If the system determines that the CCA value is greater than or equal to 5% in step  504 , then it instructs the logging and control system to continue drilling. Similarly, if the CCI is less than or equal to 0.5 in step  506 , then it instructs the logging and control system to continue drilling. However, if the CCA value is less than 5% in step  504 , then the system checks the TR value in step  512 , and if the TR value is less than 0.5, then the system increases GPM in step  510  till CCA is equal to 5%. But if TR value is not less than 0.5, then the system confirms GPM in step  518  and continues the drilling operation in step  524 . At step  526  of the process, the system optimizes drilling parameters including WOB, RPM and GPM, which process is also called as ‘particle swarm optimization.’ In alternate embodiment, if the CCI value is greater than 0.5, then the system checks for the YP/PV value in step  516 . If YP/PV is not equal to 3, then the system increases YP/PV value to 3 in step  514 . However, if the YP/PV value is equal to 3 in step  516 , then the system checks for the GPM value in step  522 . If the GPM value is equal to 1200, then the system returns to step  506  to check for the value of CCI. However, if the GPM is not equal to 1200, then the system increases GPM in step  520  until it reaches a 1200 value. 
     Particle swarm optimization (PSO) can be defined as computational method to enhance a given problem by performing many trials and tests to optimize a proposed solution that is relevant with a special measure of quality. The optimization process of PSO begins to have a huge number of proposed solutions that called particles, and then having these particles searched based one preferable and simple mathematical law for position of particles and velocity. The movement of proposed solution are caused through the local best-known position. Then aimed toward best matching position in search space and finally enables movement of the swarm direct to the best proposed solutions. PSO is basically attributed to Kennedy, Eberhart and Shi, (Kennedy, 1995) and (Shi, 1998), and was first intended for estimating the behavior of society, (Kennedy, 2001), as a representative style of the movement of organisms in a flock of bird or school of fish. The algorithm was simplified and it was noticed to be doing enhancement. The book by Kennedy and Eberhart, (Kennedy, 1997), describes many aspect of philosophy of PSO and intelligence of swarm. An extensive survey of application of PSO is done by Poli, (Poli, 2007) and (Poli, 2008). PSO can do a few or no assumptions about the problem that is being enhanced and makes very large spaces of proposed solutions. However, PSO cannot ensure an exact solution is ever found. Especially, PSO does not use the gradient of the problem which is being optimized, that means PSO does not ask for the enhancement of problem to be different as is required by classic optimization methods such as gradient descent and quasi-newton methods. PSO makes also the use of optimization of problems that are partially irregular, noisy, change over time, etc. 
       FIG. 6  is a table  600  showing test results obtained using a method for optimizing rate of penetration in a drilling operation, according to one or more example embodiments. As it can be seen from this table, there is significant improvement in ROP, HHPb, CCI, Vann, and YP/PV value using the methods and systems of the present disclosure. Similarly, DSE can be minimized up to 64% using the methods and systems of the present disclosure. 
       FIG. 7  is a another table  700  showing test results obtained via model trials performed in two wells using a method for optimizing rate of penetration in a drilling operation, according to one or more example embodiments. Similar to the results shown in  FIG. 6 , it can be seen from this table that there is significant improvement in ROP, HHPb, CCI, Vann, and YP/PV value using the methods and systems of the present disclosure. Additionally, DSE can be minimized up to 50% using the methods and systems of the present disclosure. 
       FIG. 8A  illustrates a graph  800  plotting depth of the borehole in feet versus rate of penetration in feet per hour prior to applying an optimization model, according to one or more example embodiments. The orange dots represent the actual ROP and the blue dots represent the measured ROP.  FIG. 8B  illustrates a graph  850  plotting depth of the borehole in feet versus rate of penetration in feet per hour after applying an optimization model, according to one or more example embodiments. The orange dots represent the actual ROP and the blue dots represent the measured ROP. As it can be seen from this graph there is significant improvement in ROP, using the optimization methods and systems of the present disclosure. 
     Similarly,  FIG. 9A  illustrates a graph  900  plotting actual rate of penetration in feet per hour versus measured rate of penetration in feet per hour prior to applying an optimization model, according to one or more example embodiments.  FIG. 9B  illustrates a graph  950  plotting actual rate of penetration in feet per hour versus measured rate of penetration in feet per hour after applying an optimization model, according to one or more example embodiments. As it can be seen from this graph the actual ROP appears to be in line with the measured ROP, using the optimization methods and systems of the present disclosure. 
       FIG. 10A  is a line graph  1000  plotting depth in feet versus actual rate of penetration (orange line) in feet per hour and measured rate of penetration (blue line) in feet per hour prior to applying an optimization model, according to one or more example embodiments.  FIG. 10B  is another line graph  1050  plotting depth in feet versus actual rate of penetration (orange line) in feet per hour and measured rate of penetration (blue line) in feet per hour after applying an optimization model, according to one or more example embodiments. As it can be seen from this graph there is significant improvement in actual and measured ROP, using the optimization methods and systems of the present disclosure. 
     The data shown in  FIGS. 8A-10B  can be screened and filtered to capture only drilling properties and mud properties, and then they can be plotted against each other to identify the relationship between them. At later stage, the data and the resulting relationships can be used to develop a model that can help ensure hole cleaning efficiency and optimized drilling rate. The results may be used to develop efficient hole cleaning and optimized drilling rate to enhance the performance significantly. In addition, it can be used as a tool that can guide drilling engineers to efficient hole cleaning and drilling rate. 
     One objective of the above disclosed systems and methods is to ensure optimum mud rheology values that have effective influence on drilling mud from the aspects of ECD, cuttings transport, shear thinning, and thixotropic properties, including adding the optimum values for “n” and “K,” the flow behavior index and consistency index, respectively, to develop an effective hole cleaning model by utilizing carrying capacity index and cutting concentration index in the annulus. 
     In some embodiment, by linking hole cleaning to drilling rate by using DSE to optimize the drilling parameters, this model can be run to prevent losses from occurring. It can also be used in conjunction with wellbore strengthening and lost circulation materials to enhance the efficiency of the mud system. 
     The systems and methods disclosed above are suitable for vertical hole sections. However, it can also be applied to deviated or horizontal hole sections as well. The systems and methods disclosed above can eliminate wiper trips, reaming trips, and pumping sweeps, increase ROP significantly, and prevent hole problems such as losses, tight spots and stuck pipe. Additionally, the systems and methods disclosed above can provide an optimized smart solution along with drilling operations to avoid the most chronic challenging hole problems encountered while drilling e.g. pipe sticking, loss circulation, and hole cleaning. 
     The above described systems and methods may be applied to any deviated and/or horizontal sections. They may also be used in conjunction with RTOC to ensure optimum performance is reflected in all other rigs. According to some embodiments, the systems and methods disclosed above can be applied any drilling activity suffering from losses, stuck pipe, well bore stability, hole cleaning, slow drilling rate, lack of optimization, and longer than usual non-productive time. The advantages of the above disclosed systems and methods include elimination of wiper trips, elimination of reaming trips, elimination of pumping sweeps, increase in ROP significantly, and prevention of hole problems like losses, tight spots, and stuck pipes. The technical solution provided by the systems and methods disclosed above include ensuring optimum mud rheology and bit hydraulics, developing effective hole cleaning model by utilizing carrying capacity index and cutting concentration index in annulus, linking hole cleaning to drilling rate, improving drilling rate, and optimizing the drilling parameters. 
     The Specification, which includes the Summary, Brief Description of the Drawings and the Detailed Description, and the appended Claims refer to particular features (including process or method steps) of the disclosure. Those of skill in the art understand that the invention includes all possible combinations and uses of particular features described in the Specification. Those of skill in the art understand that the disclosure is not limited to or by the description of embodiments given in the Specification. 
     Those of skill in the art also understand that the terminology used for describing particular embodiments does not limit the scope or breadth of the disclosure. In interpreting the Specification and appended Claims, all terms should be interpreted in the broadest possible manner consistent with the context of each term. All technical and scientific terms used in the Specification and appended Claims have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs unless defined otherwise. 
     As used in the Specification and appended Claims, the singular forms “a,” “an,” and “the” include plural references unless the context clearly indicates otherwise. The verb “comprises” and its conjugated forms should be interpreted as referring to elements, components or steps in a non-exclusive manner. The referenced elements, components or steps may be present, utilized or combined with other elements, components or steps not expressly referenced. 
     Conditional language, such as, among others, “can,” “could,” “might,” or “may,” unless specifically stated otherwise, or otherwise understood within the context as used, is generally intended to convey that certain implementations could include, while other implementations do not include, certain features, elements, and/or operations. Thus, such conditional language generally is not intended to imply that features, elements, and/or operations are in any way required for one or more implementations or that one or more implementations necessarily include logic for deciding, with or without user input or prompting, whether these features, elements, and/or operations are included or are to be performed in any particular implementation. 
     The systems and methods described herein, therefore, are well adapted to carry out the objects and attain the ends and advantages mentioned, as well as others inherent therein. While example embodiments of the system and method have been given for purposes of disclosure, numerous changes exist in the details of procedures for accomplishing the desired results. These and other similar modifications may readily suggest themselves to those skilled in the art, and are intended to be encompassed within the spirit of the system and method disclosed herein and the scope of the appended claims.