Efficient Wellbore Optimization Through Rock Property Analysis and Evaluation

2021 ◽  
Author(s):  
Joshua Oluwayomi Ogunrinde
Keyword(s):  
Poisson’S Ratio ◽  
Rock Strength ◽  
Wellbore Stability ◽  
Poisson's Ratio ◽  
Drilling Mud ◽  
Rock Property ◽  
Analysis And Evaluation ◽  
Property Analysis ◽  
Sonic Log ◽  
Well Data

Abstract There are numerous problems encountered during drilling such as wellbore instability, drilling mud weight estimation, as well as selecting good casing and bit for the drilling operations. It is therefore important to understand and accurately determine the strength of the rock in order to avoid these common drilling problems which are mostly encountered during well operations. It is of paramount importance to determine uniaxial compressive strength (UCS) from core and sonic log data so as to accurately predict rock strength for better well planning. In this work, we were able to obtain a correlation to determine UCS from data obtained from ten (10) wells in different locations in onshore Niger Delta using the regression analysis method. The correlation of UCS versus Poisson's ratio gave R2 value of 90.0%. The R2- value tending towards one (1) indicates that this model can be reliably used to predict ND-UCS and the p<0.05 shows that there is significant relationship between ND-UCS and Poisson's ratio. The model was validated with an entirely different well data and it predicted over 89% rock UCS data when compared to the actual rock UCS data. This study also provides an understanding of the variation in UCS and Poisson's ratio with depth for effective rock property analysis and evaluation. These correlations will help well engineers to make informed decisions on rock strength predictions during well planning and operations as well as manage wellbore stability optimally.

scholarly journals Determination of the mud weight window, optimum drilling trajectory, and wellbore stability using geomechanical parameters in one of the Iranian hydrocarbon reservoirs

2021 ◽  
Author(s):  
Masoud Hoseinpour ◽  
Mohammad Ali Riahi
Keyword(s):  
Young’S Modulus ◽  
Poisson’S Ratio ◽  
Young's Modulus ◽  
Horizontal Stress ◽  
Wellbore Stability ◽  
Poisson's Ratio ◽  
Drilling Mud ◽  
Geomechanical Parameters ◽  
Weight Window ◽  
Gurpi Formation

AbstractThe challenges behind this research were encountered while drilling into the Ilam, Mauddud, Gurpi, and Mishrif Formations, where severe drilling instability-related issues were observed across the weaker formations above the reservoir intervals. In this paper, geomechanical parameters were carried out to determine optimum mud weight windows and safe drilling deviation trajectories using the geomechanical parameters. We propose a workflow to determine the equivalent mud window (EMW) that resulted in 11.18–12.61 ppg which is suitable for Gurpi formation and 9.36–13.13 ppg for Ilam and Mishrif Formations, respectively. To estimate safe drilling trajectories, the Poisson’s ratio, Young’s modulus, and unconfined compressive strength (UCS) parameters were determined. These parameters illustrate an optimum drilling trajectory angle of 45° (Azimuth 277°) for the Ilam to Mauddud Formations and less than 35° for the Gurpi Formation. Our analysis reveals that maximum horizontal stress and Poisson’s ratio have the most impact on determining the optimum drilling mud weight windows and safe drilling deviation trajectories. On the contrary, vertical stress and Young’s modulus have minimum impact on drilling mud weight windows and safe drilling deviation trajectories. This study can be used as a reference for the optimal mud weight window to overcome drilling instability issues in future wellbore planning in the study.

Can gas sand have a large Poisson’s ratio?

Geophysics ◽  
2008 ◽  
Vol 73 (2) ◽  
pp. E51-E57 ◽  
Author(s):  
Jack P. Dvorkin
Keyword(s):  
Poisson’S Ratio ◽  
Elastic Anisotropy ◽  
Laboratory Data ◽  
Poor Quality ◽  
Poisson's Ratio ◽  
Quality Data ◽  
Poor Quality Data ◽  
Well Data ◽  
Seismic Scale

Laboratory data supported by granular-medium and inclusion theories indicate that Poisson’s ratio in gas-saturated sand lies within a range of 0–0.25, with typical values of approximately 0.15. However, some well log measurements, especially in slow gas formations, persistently produce a Poisson’s ratio as large as 0.3. If this measurement is not caused by poor-quality data, three in situ situations — patchy saturation, subresolution thin layering, and elastic anisotropy — provide a plausible explanation. In the patchy saturation situation, the well data must be corrected to produce realistic synthetic seismic traces. In the second and third cases, the effect observed in a well is likely to persist at the seismic scale.

Wellbore Stability Beyond Mud Weight

2021 ◽  
Author(s):  
Khaqan Khan ◽  
Mohammad Altwaijri ◽  
Sajjad Ahmed
Keyword(s):  
Oil And Gas ◽  
Rock Strength ◽  
Tectonic Stress ◽  
Strength Properties ◽  
Wellbore Stability ◽  
Drilling Mud ◽  
Stress Regime ◽  
Drilling Parameters ◽  
Well Trajectory ◽  
Formation Pore Pressure

Abstract Drilling oil and gas wells with stable and good quality wellbores is essential to minimize drilling difficulties, acquire reliable openhole logs data, run completions and ensure well integrity during stimulation. Stress-induced compressive rock failure leading to enlarged wellbore is a common form of wellbore instability especially in tectonic stress regime. For a particular well trajectory, wellbore stability is generally considered a result of an interplay between drilling mud density (i.e., mud weight) and subsurface geomechanical parameters including in-situ earth stresses, formation pore pressure and rock strength properties. While role of mud system and chemistry can also be important for water sensitive formations, mud weight is always a fundamental component of wellbore stability analysis. Hence, when a wellbore is unstable (over-gauge), it is believed that effective mud support was insufficient to counter stress concentration around wellbore wall. Therefore, increasing mud weight based on model validation and calibration using offset wells data is a common approach to keep wellbore stable. However, a limited number of research articles show that wellbore stability is a more complex phenomenon affected not only by geomechanics but also strongly influenced by downhole forces exerted by drillstring vibrations and high mud flow rates. Authors of this paper also observed that some wells drilled with higher mud weight exhibit more unstable wellbore in comparison with offset wells which contradicts the conventional approach of linking wellbore stability to stresses and rock strength properties alone. Therefore, the objective of this paper is to analyze wellbore stability considering both geomechanical and drilling parameters to explain observed anomalous wellbore enlargements in two vertical wells drilled in the same field and reservoir. The analysis showed that the well drilled with 18% higher mud weight compared with its offset well and yet showing more unstable wellbore was, in fact, drilled with more aggressive drilling parameters. The aggressive drilling parameters induce additional mechanical disturbance to the wellbore wall causing more severe wellbore enlargements. We devised a new approach of wellbore stability management using two-pronged strategy. It focuses on designing an optimum weight design using geomechanics to address stress-induced wellbore failure together with specifying safe limits of drilling parameters to minimize wellbore damage due to excessive downhole drillstring vibrations. The findings helped achieve more stable wellbore in subsequent wells with hole condition meeting logging and completion requirements as well as avoiding drilling problems.

Wellbore-Stability Analysis by Integrating a Modified Hoek-Brown Failure Criterion With Dual-Porochemoelectroelastic Theory (includes associated erratum)

SPE Journal ◽  
2019 ◽  
Vol 24 (05) ◽  
pp. 1957-1981 ◽  
Author(s):  
Chao Liu ◽  
Yanhui Han ◽  
Hui–Hai Liu ◽  
Younane N. Abousleiman
Keyword(s):  
Stability Analysis ◽  
Pore Pressure ◽  
Failure Criterion ◽  
Rock Strength ◽  
Chemical Potential ◽  
Wellbore Stability ◽  
Natural Fracture ◽  
Analysis Tool ◽  
Drilling Mud

Summary When drilling through naturally fractured formations, the existence of natural fractures affects the fluid diffusion and stress distribution around the wellbore and induces degradation of rock strength. For chemically active formations, such as shale, the chemical–potential difference between the drilling mud and the shale–clay matrix further complicates the nonmonotonic coupled pore–pressure processes in and around the wellbore. In this work, we apply a recently formulated theory of dual–porosity/permeability porochemoelectroelasticity to predict the time evolution of mud–weight windows, while calculating stresses and pore pressure around an inclined wellbore drilled in a fractured shale formation. The effects of natural–fracture geometric and spatial distributions coupled with the chemical activity are considered in the wellbore–stability analysis. To account for the degrading effect of the fractured shale matrix on the bulk rock strength, a modified Hoek–Brown (MHB) criterion is developed to more closely describe the in–situ state of stress effects on the compressive shearing strength at great depth. Compared with the original Hoek–Brown (HB) failure criterion, the MHB criterion considers the influence of the intermediate principal stress and thus shows better agreement with true–triaxial data for various rocks at varying stress levels. The MHB criterion converges to the original HB criterion when the confining in–situ stresses are equal. Two field case studies indicate that this novel integrative methodology is capable of predicting the operational drilling–mud–weight windows used in these two cases. Another advantage of this newly developed technique is that it can be used as a back–analysis tool to estimate the fracture–matrix permeability from field operational data.

scholarly journals Real-time prediction of Poisson’s ratio from drilling parameters using machine learning tools

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Osama Siddig ◽  
Hany Gamal ◽  
Salaheldin Elkatatny ◽  
Abdulazeez Abdulraheem
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Poisson’S Ratio ◽  
Wellbore Stability ◽  
Additional Cost ◽  
Poisson's Ratio ◽  
Inference System ◽  
Time Prediction ◽  
Drilling Parameters ◽  
Data Points

AbstractRock elastic properties such as Poisson’s ratio influence wellbore stability, in-situ stresses estimation, drilling performance, and hydraulic fracturing design. Conventionally, Poisson’s ratio estimation requires either laboratory experiments or derived from sonic logs, the main concerns of these methods are the data and samples availability, costs, and time-consumption. In this paper, an alternative real-time technique utilizing drilling parameters and machine learning was presented. The main added value of this approach is that the drilling parameters are more likely to be available and could be collected in real-time during drilling operation without additional cost. These parameters include weight on bit, penetration rate, pump rate, standpipe pressure, and torque. Two machine learning algorithms were used, artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS). To train and test the models, 2905 data points from one well were used, while 2912 data points from a different well were used for model validation. The lithology of both wells contains carbonate, sandstone, and shale. Optimization on different tuning parameters in the algorithm was conducted to ensure the best prediction was achieved. A good match between the actual and predicted Poisson’s ratio was achieved in both methods with correlation coefficients between 0.98 and 0.99 using ANN and between 0.97 and 0.98 using ANFIS. The average absolute percentage error values were between 1 and 2% in ANN predictions and around 2% when ANFIS was used. Based on these results, the employment of drilling data and machine learning is a strong tool for real-time prediction of geomechanical properties without additional cost.

scholarly journals The Geomechanics and the Acoustic Anisotropy of Reservoir Rocks

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Ahmed Zarzor Al-Yaseri
Keyword(s):  
Bulk Modulus ◽  
Young’S Modulus ◽  
Poisson’S Ratio ◽  
Reservoir Characterization ◽  
Young's Modulus ◽  
Petroleum Industry ◽  
Wellbore Stability ◽  
Production Performance ◽  
Acoustic Properties ◽  
Poisson's Ratio

Knowing the mechanical properties (Young’s modulus (E)( , Poisson’s Ratio (ν), Shear Modulus (G), Bulk modulus (K) and compressibility which is the inverse of Bulk modulus) of the rocks involve in a reservoir, are critical factors for reservoir characterization). Those properties affect a wide variety of applications into the petroleum industry; from drilling well planning and execution to production performance (sand production, compaction, subsidence, etc) passing through a wide variety of topics like wellbore stability, well completions and of course reservoir characterization. For these reasons, the knowledge of these properties is really valuable for people working in the petroleum industry and of course working in reservoir characterization. This study was located in Berea town, Oklahoma, and it was intended to identify the geomechanical and acoustic properties of a sandstone sample. The Berea sandstone elastic properties are characterized using two methods: Quasi static and Dynamic. A detailed explanation of the sample preparation and the testing procedure is provided. Calculation results for both methods showed consistent values for the Young’s modulus being around 3,000,000 psi. The Poisson’s Ratio value is between 0.13 and 0.3. This study was performed in the PoroMechanics Institute (PMI) in the Sarkeys Energy Center at the University of Oklahoma, USA. Monitoring equipment was used to obtain all the information necessary for the proper characterization of the rock. The results of this work are a good tool that can be used in future simulations such as hydraulic fracturing treatment, reservoir fluid flow or reserve estimation.

Applying Different Artificial Intelligence Techniques in Dynamic Poisson's Ratio Prediction Using Drilling Parameters

2021 ◽  
pp. 1-15
Author(s):  
Osama Sidddig ◽  
Hany Gamal ◽  
Salaheldin Elkatatny ◽  
Abdulazeez Abdulraheem
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Poisson’S Ratio ◽  
Correlation Coefficients ◽  
Wellbore Stability ◽  
Performance Estimation ◽  
Poisson's Ratio ◽  
Support Vector ◽  
Drilling Parameters ◽  
Data Points

Abstract Rock geomechanical properties impact wellbore stability, drilling performance, estimation of in-situ stresses, and design of hydraulic fracturing. One of these properties is Poisson's ratio which is measured from lab testing or derived from well logs, the former is costly, time-consuming and doesn't provide continuous information, and the latter may not be always available. An alternative prediction technique from drilling parameters in real-time is proposed in this paper. The novel contribution of this approach is that the drilling data is always available and obtained from the first encounter with the well. These parameters are easily obtainable from drilling rig sensors such as rate of penetration, weight on bit and torque. Three machine-learning methods were utilized, support vector machine (SVM), functional network (FN) and random forest (RF). Dataset (2905 data points) from one well were used to build the models, while a dataset from another well with 2912 data points was used to validate the constructed models. Both wells have diverse lithology consists of carbonate, shale and sandstone. To ensure optimal accuracy, sensitivity and optimization tests on various parameters in each algorithm were performed.The three machine learning tools provided good estimations, however, SVM and RF yielded close results, with correlation coefficients of 0.99 and the average absolute percentage error (AAPE) values were mostly less than 1%. While in FN the outcomes were less efficient with correlation coefficients of 0.92 and AAPE around 3.8%. Accordingly, the presented approach provides an effective tool for Poisson's ratio prediction on a real-time basis at no additional expense. In addition, the same approach could be used in other rock mechanical properties.

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