A Real-Time Indicator for the Evaluation of Hole Cleaning Efficiency

2019 ◽  
Author(s):  
Mohammed Alawami ◽  
Mohammed Bassam ◽  
Salem Gharbi ◽  
Mohammed Al Rubaii
2021 ◽  
Author(s):  
Mohammed M Al-Rubaii ◽  
Dhafer Al-Shehri ◽  
Mohamed N Mahmoud ◽  
Saleh M Al-Harbi ◽  
Khaled A Al-Qahtani

Abstract Hole cleaning efficiency is one of the major factors that affects well drilling performance. Rate of penetration (ROP) is highly dependent on hole cleaning efficiency. Hole cleaning performance can be monitored in real-time in order to make sure drilled cuttings generated are efficiently transported to surface. The objective of this paper to present a real time automated model to obtain hole cleaning efficiency and thus effectively adjust parameters as required to improve drilling performance. The process adopts a modified real time carrying capacity indicator. There are many hole cleaning models, methodologies, chemicals and correlations, but majority of these models do not simulate drilling operations sequences and are not dependent on practicality of drilling operations. The developed real time hole cleaning indicator can ensure continuous monitoring and evaluation of hole cleaning performance during drilling operations. The methodology of real time model development is by selecting offset mechanical drilling parameters and drilling fluid parameters where collected, analyzed, tested and validated to model strong hole cleaning efficiency indicator that can extremely participate and facilitate a position in drilling automations and fourth industry revolution. The automated hole cleaning model is utilizing real time sensors of drilling and validate the strongest relationships among the variables. The study, analysis, test and validation of the relationships will reveal the significant parameters that will contribute massively for model development procedures. The model can be run as well by using the real time sensors readings and their inputs to be fed into the developed automated model. The developed model of real time carrying capacity indicator profile will be shown as function of depth, drilling fluid density, flow rate of mud pump or mud pump output, and other important factors will be illustrated by details. The model has been developed and validated in the field of drilling operations to empower the drilling teams for better and understandable monitoring and evaluation of hole cleaning efficiency while performing drilling operations. The real time model can provide a vision for better control of mud additives and that will contribute to mud cost effectiveness. The automated model of hole cleaning efficiency optimized the rate of penetration (ROP) by 50% in well drilling performance as a noticeable and valuable improvement. This optimum improvement saved cost and time of rig and drilling of wells and contributed to accelerate wells’ delivery. The innovative real time model was developed to optimize drilling and operations efficiency by using the surface rig sensors and interpret the downhole measurements and that can lead innovatively to other important hole cleaning indicators and other tactics for better development of downhole measurements models that can participate for optimized drilling efficiency.


2021 ◽  
Vol 73 (05) ◽  
pp. 63-64
Author(s):  
Chris Carpenter

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 203147, “Investigating Hole-Cleaning Fibers’ Mechanism To Improve Cutting Carrying Capacity and Comparing Their Effectiveness With Common Polymeric Pills,” by Mohammad Saeed Karimi Rad, Mojtaba Kalhor Mohammadi, SPE, and Kourosh Tahmasbi Nowtarki, International Drilling Fluids, prepared for the 2020 Abu Dhabi International Petroleum Exhibition and Conference, Abu Dhabi, held virtually 9–12 November. The paper has not been peer reviewed. Hole cleaning in deviated wells is more challenging than in vertical wells because of the boycott effect or the eccentricity of the drillpipe. Poor hole cleaning can result in problems such as borehole packoff or excessive equivalent circulating density. The complete paper investigates a specialized fibrous material (Fiber 1) for hole-cleaning characteristics. The primary goal is to identify significant mechanisms of hole-cleaning fibers and their merits compared with polymeric high-viscosity pills. Hole-Cleaning Indices Based on a review of the literature, most effective parameters regarding hole cleaning in different well types were investigated. These parameters can be classified into the following five categories: - Well design (e.g., hole angle, drillpipe eccentricity, well trajectory) - Drilling-fluid properties (e.g., gel strength, mud weight) - Formation properties (e.g., lithology, cutting specific gravity, cuttings size and shape) - Hydraulic optimizations (e.g., flow regime, nozzle size, number of nozzles) - Drilling practices (e.g., drillpipe rotation speed, wellbore tortuosity, bit type, rate of penetration, pump rate) In this research, rheological parameters and parameters of the Herschel-Bulkley rheological model are considered to be optimization inputs to increase hole-cleaning efficiency of commonly used pills in drilling operations. The complete paper offers a detailed discussion of both the importance of flow regime and the role of the Herschel-Bulkley rheological model in reaching a better prognosis of drilling-fluid behavior at low shear rates. The properties of the fibrous hole-cleaning agent used in the complete paper are provided in Table 1. Test Method Two series of tests were performed. The medium of the first series is drilling water, with the goal of evaluating the efficiency of Fiber 1 in fresh pills. The second series of tests was per-formed with a simple polymeric mud as a medium common in drilling operations. Formulations and rheological properties of both test series are provided in Tables 4 and 5 of the complete paper, respectively.


2021 ◽  
Author(s):  
Pradeepkumar Ashok ◽  
John D' Angelo ◽  
Dawson Ramos ◽  
Michael Yi ◽  
Taylor Thetford ◽  
...  

Abstract Hole cleaning is important in preventing stuck pipe events during well construction operations. A cuttings transport model is traditionally used to determine the cleanliness of a hole, but its real-time rig site implementation is often made difficult by a lack of necessary inputs. There is a need for a simpler yet reliable approach to quantifying hole cleanliness using data readily available at the rig site. The paper proposes a method that relies on the detection of events over a long time horizon and the use of key parameters relating to such events to quantify hole cleanliness. These events are then related through duration and frequency to probabilistic features in a Bayesian network, to infer the probability that the hole cleaning process has been efficient or poor. These events are also weighted by their age to ensure that current beliefs are not strongly influenced by those that are far in the past. The method was deployed on a drilling advisory system and is currently used on rigs in North American land operations. The events and features found to be most relevant to quantifying hole cleanliness were the circulation rates during drilling, tight spots when moving the drillstring, bit hydraulics, and prolonged periods of inactivity. Proactive hole cleaning actions such as working of the pipe, off bottom circulation and pipe rotation were also considered. The Bayesian network model used by the proposed method was able to be run with low computational overhead (micro-seconds on a standard edge device) compared to a traditional cuttings transport model. This was enabled by an event logging procedure that keeps track of hole-cleaning events over time and consolidates several hours (days) of drilling information into relevant hole-cleaning features that can be processed quickly. The proposed method was validated with statistical methods using surface datasets from six wells involved in North American land operations. Through this validation it was determined that the method was highly effective in correctly characterizing hole conditions throughout the well operation. On the rig, the system was helpful in not only in alerting the drillers whenever hole cleanliness deteriorated but also providing the most likely causes of the deterioration. This provided the rig crew real-time guidance to make actionable decisions to avoid a stuck pipe situation. The proposed method differentiates itself from the published methods of hole cleaning analysis in two main aspects. First, it does not presume to estimate the cuttings bed height or accumulation over time. Instead, it attempts to infer the probability that the hole cleaning operations are effective over time using features in data that suggest efficient or poor hole cleaning. Second, this method provides a clear indication of when hole cleaning actions are needed and why.


2003 ◽  
Author(s):  
A.L. Martins ◽  
M.B. Villas-Boas ◽  
H.S. Taira ◽  
A.F. Aragão ◽  
R.A.F. Amorim ◽  
...  

2013 ◽  
Author(s):  
E. Cayeux ◽  
T. Mesagan ◽  
S. Tanripada ◽  
M. Zidan ◽  
K. K. Fjelde

2021 ◽  
pp. 1-11
Author(s):  
Ahmed K. Abbas ◽  
Mortadha T. Alsaba ◽  
Mohammed F. Al Dushaishi

Abstract Extended reach (ERD) wells with a horizontal and highly deviated section are widely applied in the oil and gas industry because they provide higher drainage area than vertical wells; and hence, increase the productivity or injectivity of the well. Among many issues encountered in a complex well trajectory, poor hole cleaning is the most common problem, which occurs mainly in the deviated and horizontal section of oil and gas wells. There are significant parameters that have a serious impact on hole cleaning performance in high-angle and horizontal sections. These include flow rate, rheology and density of the drilling fluid, drillstring eccentricity, pipe rotation, and cuttings size. It has been recognized that the action of most of these parameters to transport drilled cuttings is constantly a point of controversy among oilfield engineers. In the present study, extensive experiments were conducted in an advanced purpose-built flow rig to identify the main parameters affecting on circulate the cuttings out of the test section in a horizontal position. The flow-loop simulator has been designed to allow easy variation of operational parameters in terms of flow rate, mud density, drillstring eccentricity, pipe rotation, and cuttings size. In addition, the study covers the impacts of laminar, transition, and turbulent flow regimes. The goal of such variation in the operational conditions is to simulate real field situations. The results have shown that drill string rotation and flow rate were the operational parameters with the highest positive influence on the cuttings transports process. In contrast, drill pipe eccentricity has a negative influence on cuttings removal efficiency. The cuttings transportation performance is further improved by pipe rotation at different levels of eccentricity, especially at fully eccentric annuli. It was also shown that larger cuttings appeared to be easier to remove in a horizontal annulus than smaller ones. The experimental results would provide a more in-depth understanding of the relationship between drilling operation parameters and hole cleaning efficiency in ERD operations. This will help the drilling teams to realize what action is better to take for efficient cutting transportation.


2015 ◽  
Author(s):  
Mike Okot ◽  
Marlio Campos ◽  
German Muñoz ◽  
Alawi G Alalsayednassir ◽  
Matt Weber ◽  
...  

2021 ◽  
Author(s):  
Ashabikash Roy Chowdhury ◽  
Matthew Forshaw ◽  
Narender Atwal ◽  
Matthias Gatzen ◽  
Salman Habib ◽  
...  

Abstract In the increasingly complex and cost sensitive drilling environment of today, data gathered using downhole and surface real-time sensor systems must work in unison with physics-based models to facilitate early indication of drilling hazards, allowing timely action and mitigation. Identification of opportunities for reduction of invisible lost time (ILT) is similarly critical. Many similar systems gather and analyze either surface or downhole data on a standalone basis but lack the integrated approach towards using the data in a holistic decision-making manner. These systems can either paint an incomplete picture of prevailing drilling conditions or fail to ensure system messages result in parameter changes at rigsite. This often results in a hit or miss approach in identification and mitigation of drilling problems. The automated software system architecture is described, detailing the physics-based models which are deployed in real-time consuming surface and downhole sensor data and outputting continuous, operationally relevant simulation results. Measured data from either surface, for torque & drag, or downhole for ECD & ESD is then automatically compared both for deviation of actual-to-plan, and for infringement of boundary conditions such as formation pressure regime. The system is also equipped to model off-bottom induced pressures; swab & surge, and dynamically advise on safe, but optimum tripping velocities for the operation at hand. This has dual benefits; both the avoidance of costly NPT associated with swab & surge, as well as being able to visually highlight running speed ILT. All processing applications are coupled with highly intuitive user interfaces. Three successful deployments all onshore in the Middle East are detailed. First a horizontal section where real-time model vs. actual automatic comparison of torque & drag samples, validated with PWD data allowed early identification of poor hole cleaning. Secondly, a vertical section where again the model vs. actual algorithmic automatically identified inadequate hole cleaning in a case where conventional human monitoring did not. Finally, a case is exhibited where real-time modelling of swab and surge, as well as intuitive visualization of the trip speeds within those boundary conditions led to a significant increase in average tripping speeds when compared to offset wells, reducing AFE for the operator. Common for all three deployments was an integrated well services approach, with a single service company providing the majority of services for well construction, as well as an overarching remote operations team who were primary users of the software solutions deployed.


2020 ◽  
Author(s):  
Oliver Czuprat ◽  
Anne Marte Faugstad ◽  
Piotr Byrski ◽  
Kai Schulze

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