Analysis of drilling difficulty of extended-reach wells based on drilling limit theory

Huang, Wenjun; Gao, Deli

doi:10.1016/j.petsci.2021.12.030

Cited by 12 publications

(6 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Inspired by the above analysis, this paper puts forward a data-based integrated evaluation model for offshore oil development. The major data sources include the National Bureau of Statistics of China [31], field practice data, industry statistics, and technical literature [32][33][34]. Based on the actual project data of the oil field, the model can conduct economic evaluations on the development of offshore oil projects and provide data demonstration and theoretical support for decision makers on whether to invest in the project.…”

Section: Contributionsmentioning

confidence: 99%

“…In this way, the structure of the submodel can be determined, including model variable types (main factors) and model coefficients (influence degree). The data originate from the National Bureau of Statistics of China [31], field practice data, industry statistics, and technical literature [32][33][34]. The specific multiple regression method is shown in Appendix A.…”

Section: Regression Analysismentioning

confidence: 99%

See 1 more Smart Citation

A Realistic and Integrated Model for Evaluating Offshore Oil Development

Qiu

Zhang

et al. 2022

JMSE

View full text Add to dashboard Cite

With the rising consumption of oil resources, major oil companies around the world have increasingly engaged in offshore oil exploration and development, and offshore oil resources have accounted for an increasing proportion. Offshore oil engineering projects are capital intensive, and the development of offshore oil fields faces a tough battle, especially in a period of low oil prices. Thus, a comprehensive evaluation model is highly needed to help assess economic benefits and provide meaningful and valuable information for operators and investors to make sensible decisions. This study firstly proposed a realistic and integrated evaluation model for offshore oil development based on actual historical project data. This evaluation model incorporated modules from the underwater system to the platform system and processes from oil reservoir extraction to oil, gas and water treatment. The uncertain parameters in the evaluation process are dealt with by sensitivity analysis and Monte Carlo simulation. The proposed model is applied to a typical offshore oil development project in Bohai Bay, China. The results reveal that the recovery factor and oil price have the greatest impact on the economic benefits. In the case of deterministic analysis, the breakeven oil price of the project is 40.59 USD/bbl. After considering the uncertainty of project parameters, the higher the oil price, the greater the probability of NPV > 0. When the oil price is higher than 70 USD/bbl, even with uncertain project parameters, the probability of NPV > 0 can still be as high as 97.39%.

show abstract

Section: Contributionsmentioning

confidence: 99%

Section: Regression Analysismentioning

confidence: 99%

A Realistic and Integrated Model for Evaluating Offshore Oil Development

Qiu

Zhang

et al. 2022

JMSE

View full text Add to dashboard Cite

show abstract

“…Extended reach wells refer to drilling operations that involve reaching reservoir targets located at considerable distances from the surface drilling location . These wells typically have high horizontal sections and can extend for several kilometers . The primary objective of extended reach wells is to access remote or hard-to-reach hydrocarbon reserves while minimizing the number of surface locations and drilling costs. , One of the significant challenges associated with extended reach wells is the risk of shale swelling when exposed to different water-based drilling fluids (WBDFs) .…”

Section: Introductionmentioning

confidence: 99%

An Experimental Study and Machine Learning Modeling of Shale Swelling in Extended Reach Wells When Exposed to Diverse Water-Based Drilling Fluids

Tariq,

Murtaza,

Alrasheed

et al. 2024

Energy Fuels

View full text Add to dashboard Cite

Shale swelling poses considerable challenges for companies involved in extended-reach well drilling, particularly when it comes to maintaining wellbore stability. Despite the incorporation of swelling inhibitors in water-based drilling fluids (WBDFs), shale swelling can persist as an issue. Currently, the assessment of WBDFs' ability to prevent swelling usually involves costly, timeconsuming, and labor-intensive laboratory experiments. Therefore, this study leverages machine learning techniques (ML) to forecast the dynamic linear swelling behavior of sodium bentonite-based shale wafers. These shale wafers were subjected to different WBDFs containing diverse inorganic salts such as sodium chloride (NaCl), potassium chloride (KCl), magnesium chloride (MgCl 2 ), and calcium chloride (CaCl 2 ). To gather sufficient data to train the ML models, an extensive experimental study was conducted using various WBDF formulations. The experiments were conducted on wafers, wherein each wafer treated with an inorganic salt underwent a linear swell test for 120 h until the swelling reached a plateau. Moreover, the conductivities and zeta potential of WBDFs, which were prepared using varying concentrations of salts, were recorded. Several ML techniques, namely gradient boosting, decision trees, adaptive gradient boosting (AdaBoost), K-nearest neighbors, random forest, extreme gradient boosting, and stacked generalized regression (SGR) were used to forecast shale swelling. The ML models were trained using input features such as salt types, salt concentrations, salt conductivities, salt zeta potential, and elapsed time. The results revealed that the SGR model outperformed other techniques by effectively predicting linear swelling in terms of coefficient of determination (R 2 ) above 0.95. The developed ML model offers an efficient approach to assess the maximum swelling potential of various WBDFs that can help in effectively mitigating the wellbore instability concerns by continuously evaluating the interaction between shale and the drilling fluid for drilling for extended reach or maximum contact wells.

show abstract

“…Lesage et al used the soft rod model to invert the friction coefficient by combining the ground hook load, rotary table torque, weight on bit and bit torque to identify drilling abnormal conditions, in which the values of WOB and bit torque were obtained by downhole measurement, but the real-time data transmission could not be realized [3]. Huang Wenjun et al established a friction torque model considering the effect of the pipe string joints, which can more accurately simulate the complex mechanical behavior of the drill string with joints in the wellbore [4].…”

Section: Introductionmentioning

confidence: 99%

Research on the prediction of drag and torque based on BP algorithm

Fan

Hua

et al. 2023

Third International Seminar on Artificial Intelligence, Networking, and Information Technology (AINIT 2022)

View full text Add to dashboard Cite

In the current oil fields in China, the horizontal well technology with a long horizontal interval has gradually become the core technology to develop conventional oil and gas reservoirs, and the accurate determination of the drag and torque of the drill string is the key. However, the determination of the friction coefficient is affected by many factors, and it is difficult to describe it clearly by mathematical formulas. According to the characteristics of friction factors, the method of calculating the friction coefficient of drill string is studied, and a prediction model of friction coefficient based on BP algorithm is established. Based on the predicted friction coefficient, the calculation method of drag and torque is analyzed, and a drag and torque prediction model based on BP algorithm is established. The experimental results show that the use of BP neural network can accurately predict the friction coefficient and torque, and the prediction of the friction coefficient can characterize the risk of sticking of the drill string to a certain extent, which facilitates the adjustment of drilling parameters on site to improve the safety during drilling.

show abstract

Analysis of drilling difficulty of extended-reach wells based on drilling limit theory

Cited by 12 publications

References 25 publications

A Realistic and Integrated Model for Evaluating Offshore Oil Development

A Realistic and Integrated Model for Evaluating Offshore Oil Development

An Experimental Study and Machine Learning Modeling of Shale Swelling in Extended Reach Wells When Exposed to Diverse Water-Based Drilling Fluids

Research on the prediction of drag and torque based on BP algorithm

Contact Info

Product

Resources

About