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Results
Failure Analysis and Countermeasures for Cement Sheath Interface Sealing Integrity in Shale Gas Wells
Li, Jin (State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University) | Liu, Jian (State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University (Corresponding author)) | Li, Zaoyuan (State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University) | Liu, Yang (CCDC Downhole Operation Company) | Yu, Caijun (CCDC Downhole Operation Company) | Song, Weitao (State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University) | Wu, Xuning (State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University) | Yang, Fujie (State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University) | Su, Donghua (State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University)
Summary Shale gas development usually uses large displacement horizontal well and staged fracturing technology to increase operation production. The complex environmental and construction conditions often lead to wellbore sealing integrity problems in the shale gas production process. This study shows a new method for evaluating the sealing integrity of shale gas cement sheath interfaces, which aims to understand the failure mechanism during shale gas production and to propose countermeasures that can effectively improve the sealing integrity of cement sheath interfaces in shale gas cementing. The study results showed that the oil contamination of cement sheath interface will greatly weaken its sealing performance. After repeated cyclic loading, the sealing performance of the conventional and expanded cement sheath assemblies is damaged, and a gas channel is formed, which is caused by the combination of microcracks and microgaps. Furthermore, oil contamination of the cement sheath interface will accelerate its sealing failure. The addition of an expansion agent is helpful to solve the problem of microgap destruction, and the fibers or whiskers can alleviate the problem of tensile cracking. The field application in the three wells proved that the toughened expanded cement slurry significantly improved the sealing integrity of the cement sheath interface in shale gas wells. The research results can evaluate and predict the sealing performance of the cement sheath interface in shale gas wells under the conditions of staged fracturing and have some directional significance for the cement slurry system optimization in the field.
Perfect Infill Drilling and Geosteering with Hybrid Rotary Steerable System and Novel Ultra-Deep Resistivity High-Definition Mapping Technology โ A Case Study from Offshore Australia
Hoeyland, Henning (Jadestone Energy) | Bakar, Aida (Jadestone Energy) | Iliani, Nur Shahera (Jadestone Energy) | Yeoh, Xiao Qi (Jadestone Energy) | Fadjarijanto, Ari (Jadestone Energy) | Gallagher, Brian (Jadestone Energy) | Wang, Haifeng (SLB) | Singam, Chandrasekhar Kirthi (SLB) | Liu, Yang (SLB) | Rigden, Matthew (SLB) | Jiang, Xiaohu (SLB) | Mirto, Ettore (SLB)
Abstract Stag field in the northwest shelf of offshore Australia has been in production since 1998 and recently two horizontal infill wells were planned to recover unswept oil. Well A was planned in the west part of the field in perpendicular direction to several existing wells, and well B was planned as an Extended-Reach-Drilling (ERD) well towards the east part of the field. Drilling challenges for these wells included the poorly consolidated formation in reservoir, the unstable overburden Muderong shale, the anti-collision risk for well A, and extended reach drilling operation for well B. Both wells required geosteering operation, which had the associated challenges of the depth uncertainty of top reservoir at landing, the undulating reservoir top with glauconite erosional features, the movable OWC, and the low resistivity in reservoir. A systematic approach for drilling, geosteering, and completion was required to ensure the success of this infill campaign. A new hybrid Rotary Steerable System (RSS) with the capability of delivering high-build rate with greater precision and ROP with less formation restrictions, was chosen to tackle these drilling challenges. Geosteering operation adopted a new generation Ultra-Deep Resistivity High-Definition (UDR-HD) mapping tool that can provide larger depth of investigation and higher resolution at the same time, through innovations on the measurements and inversion method. This new tool is capable of providing high-definition mapping even for reservoir with low resistivity and limited contrast with overburden shale. This capability helped the operator address challenges of landing, geosteering, and OWC mapping. The combination of the hybrid RSS and the UDR-HD tool provided a fit-for-purpose solution for these two challenging infill wells. The execution of the drilling and geosteering for both wells went smoothly. The two wells were drilled with 100% operation efficiency, achieving approximately 3km reservoir exposure in total, without issue with anti-collision and completion run. Landing was optimized thanks to remote detection of top reservoir while drilling in overburden. The clear reservoir boundaries depicted by UDR-HD mapping tool enabled the operator to make informed geosteering decisions to maximize production, while the hybrid RSS implemented these decisions accurately and reliably without compromising wellbore quality. The hybrid RSS and UDR-HD tools were used in both the 8.5-inch intermediate section and the 6ร7-inch reservoir section and delivered the desired performance for both sections. The hybrid RSS was capable of delivering required build rate regardless of formations. Even with limited resistivity contrast, the UDR-HD tool could still provide clear reservoir mapping no matter it was from inside or outside the reservoir. Further study the UDR-HD tool data also deliver more insights of features like OWC, glauconite pods, and locations of well crossings.
- Geology > Geological Subdiscipline (0.46)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Mudrock > Shale (0.45)
- Oceania > Australia > Western Australia > North West Shelf > Muderong Shale Formation (0.99)
- Oceania > Australia > Western Australia > North West Shelf > Carnarvon Basin > Dampier Basin > WA-209-P > Stag Field (0.99)
- Oceania > Australia > Western Australia > North West Shelf > Carnarvon Basin > Dampier Basin > WA-15-L > Stag Field (0.99)
- (5 more...)
- Well Drilling > Drilling Operations > Geosteering / reservoir navigation (1.00)
- Well Drilling > Drilling Operations > Directional drilling (1.00)
- Well Drilling > Drilling Equipment > Directional drilling systems and equipment (1.00)
- Management > Asset and Portfolio Management > Field development optimization and planning (1.00)
Physical Simulation and Improved Numerical Simulation Method of Non-Condensable Gas Co-Injection in SAGD Process
Liang, Guangyue (Research Institute of Petroleum Exploration and Development, CNPC) | Liu, Yang (Research Institute of Petroleum Exploration and Development, CNPC) | Xie, Qian (Research Institute of Petroleum Exploration and Development, CNPC) | Xia, Zhaohui (Research Institute of Petroleum Exploration and Development, CNPC) | Liu, Shangqi (Research Institute of Petroleum Exploration and Development, CNPC) | Zhou, Jiuning (Research Institute of Petroleum Exploration and Development, CNPC) | Bao, Yu (Research Institute of Petroleum Exploration and Development, CNPC)
Abstract There are great differences about the distribution of non-condensable gas (NCG) in steam chamber between field observations and numerical simulations. Field observations show that the process could reduce steam consumption significantly but no evidence of impairment to oil production especially in mid to late SAGD life. However, this point isn't consistent with current numerical simulations. Therefore, this paper presents an improved numerical simulation method of non-condensable gas co-injection to validate the physical simulation results. Solubility experiments of methane, nitrogen and carbon dioxide in oil phase at different pressure and temperature were conducted to analyze the interface properties, and 1D core experiments to understand the displacement characteristics. On the basis, 3D physical simulations were conducted with each gas in SAGD process. These results were inconsistent with conventional numerical simulations. In order to narrow the gap, sensitivity analysis was conducted by using CMG STARS software considering different grid size, solubility or K-value in oil and water phase, rate-dependent dissolution and ex-solution of NCG in oil. Non-equilibrium dissolution and ex-solution behavior and reaction equations were incorporated to successfully improve the numerical simulation results. The experimental tests indicate that the solubility and compressibility of methane fall in between nitrogen and carbon dioxide. Then 3D visualized physical simulations with methane, nitrogen or flue gas co-injection and shale interlayer existence were conducted to analyze the law of NCG distribution, steam chamber growth and SAGD performance. NCG tends to accumulate at the top rather than the drainage edge of steam chamber, decrease the temperature of reservoir top by about 30ยฐC, reduce heat loss to the cap rock and improve steam to oil ratio (SOR). Compared with other gases, carbon dioxide decrease oil viscosity most and achieve higher displacement efficiency. Also, it succeeds in improving the flow characteristics of steam chamber front, maintaining pressure, stabilizing or slightly lowering oil production and reducing steam injection significantly by co-injection with these NCG at increasing proportion, when steam chamber reaches the top of reservoir. Particularly, NCG can penetrate thin shale interlayer, allow steam passing through and help accelerate vertical steam chamber growth. Finally, the parameters were optimized using improved field-scale model such as solvent type, co-injection concentrations and timing, etc. The novelty of this paper is successfully revealing NCG distribution law in steam chamber by visualized physical simulations. Particularly, it also captures the phenomenon that the existence of NCG can help steam chamber penetrate the shale interlayer. The findings narrow the gap among field observations, physical and numerical simulation and can guide NCG co-injection optimization.
- Asia (0.68)
- North America > Canada > Alberta (0.49)
- Geology > Petroleum Play Type > Unconventional Play > Heavy Oil Play (0.74)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Mudrock > Shale (0.65)
Seismic data suffer from under-sampling along spatial dimensions due to physical and economic limitations during acquisition, which can adversely impact subsequent imaging processes. Various approaches have been proposed to address this issue, including rank-reduction, transform, and deep learning (DL) methods for reconstructing missing traces in observed seismic data. While many DL-based reconstruction methods employ convolutional neural networks (CNNs) as their core components in supervised or unsupervised settings, the accuracy of CNN-based DL reconstruction methods can still be enhanced due to the inherent localization of convolutional operators. In this study, we present an innovative method, termed Attentive CNN (ACNet), that incorporates a transformer model with a multi-head self-attention mechanism into the CNN framework for unsupervised seismic data reconstruction. ACNet consists of an encoder built with the transformer model and a CNN decoder, enabling an iterative reconstruction process within the proposed unsupervised DL-based approach. We compare the performance of our method with that of the damped rank-reduction (DRR) method using synthetic and field data examples. The results demonstrate that our proposed method exhibits superior signal reconstruction and random noise suppression capabilities compared to the DRR method.
The utilization of a fractional visco-acoustic equation facilitates a significantly enhanced simulation of seismic wave propagation, rendering it indispensable for seismic data interpretation and processing. However, this equation poses a challenge due to the presence of two complex fractional Laplace operators, which impose difficulties in numerical solution. Recently, Fourier neural operators (FNO) have demonstrated notable efficacy in the resolution of partial differential equations (PDEs). To enhance the predictive accuracy further, we present a novel approach that leverages the U-net Fourier neural operator (U-FNO) for solving the intricate complex fractional visco-acoustic wave equation. Diverging from FNO, U-FNO incorporates an additional U-Fourier layer after the conventional Fourier layer. This augmentation empowers U-FNO to efficiently capture the high-frequency components, thus enabling the trained U-FNO to generate highly accurate solutions for the remaining time steps. Numerical examples provide evidence that U-FNO can successfully solve the fractional visco-acoustic wave equation without explicitly considering the fractional Laplace operators. Furthermore, U-FNO achieves superior prediction accuracy compared to the conventional FNO-based method.
Compared to isotropic media, AVO inversion based on VTI media enables the acquisition of high-precision elastic parameters. Traditional inversion methods typically rely on low-frequency elastic parameters, while intelligent inversion methods often necessitate a vast number of training samples. However, the scarcity of field work area well-log data poses challenges in providing low-frequency elastic parameters and suitable training samples, consequently impacting the accuracy and resolution of inverted elastic parameter. To tackle these challenges, we employ neural network technology and propose an intelligent seismic AVO inversion method founded on the convolutional model theory. The proposed method formulates a coupled objective function, leveraging both low-frequency elastic parameters and training samples to reduce the inversionโs reliance on either, thereby yielding elastic parameters with high accuracy and resolution. Tests on field data confirm the feasibility and advancement of our proposed method.
Wellbore Stability Analysis of Inclined Shale Wells Using a Fully Anisotropic Hydraulic-Mechanical Coupled FEM Model
Qiu, Yi (Southwest Petroleum University) | Ma, Tianshou (Southwest Petroleum University) | Peng, Nian (Southwest Petroleum University) | Liu, Yang (Southwest Petroleum University) | Liu, Jinhua (Southwest Petroleum University)
ABSTRACT Shale rock is typically anisotropic in both elasticity and strength, but traditional wellbore stability models generally assume that shale rock is isotropic or partially anisotropic, and the influence of hydraulic-mechanical coupling is usually ignored, so the effect of arbitrary inclined well path on shale wellbore stability is still not fully understood. Therefore, assuming the shale to be completely anisotropic in both elasticity and strength, a hydraulic-mechanical coupled finite element model was used to investigate the effect of arbitrarily inclined well paths on the time-dependent stability of shale wellbores. The results indicated that the anisotropy of elasticity (nE=nv=2 or nE=nv=0.5) dominates the induced pore pressure and offsets/enhances the isotropic part, resulting in the induced pore pressure in an anisotropic situation being opposite/enhanced to that of the isotropic situation on the 2D cross-sectional plane of the well. As the anisotropy index of the elastic parameters increased, the effective stress increased and was deflected at a certain angle. The effective hoop stress was skewed toward higher stiffness, and the shear failure area gradually decreased. Comparison of the failure zone with different borehole trajectories showed that the influence of the bedding plane decreased when the relative angle between the borehole axis and the bedding normal was small. Therefore, avoiding drilling parallel to bedding planes is conducive to borehole stability in practical drilling. INTRODUCTION The commercial success of shale gas in North America has prompted a global interest in the development of unconventional oil and gas resources, including shale oil and gas, tight oil and gas, and coalbed methane (Ma et al. 2015; Soeder 2018; Wu et al. 2020; Nie et al. 2021). Horizontal drilling technology is an efficient method to develop unconventional oil and gas. However, during drilling operations, wellbore instability can lead to a series of time-consuming and costly accidents, such as sticking and burying (Fjar et al. 2008; Zhang 2013; Meier et al. 2015). Among them, 90% of wellbore instability occurs in shale formations because shale is rich in clay minerals and bedding planes, so shale rock has different mechanical properties in different directions, i.e., shale is typically anisotropic (Gholami and Rasoul 2014; Barton and Quadros 2015; Ma et al. 2020). Anisotropy makes the wellbore more prone to collapse and instability. Therefore, it is necessary to better understand the wellbore instability mechanisms in anisotropic formations.
- North America > United States (1.00)
- Asia > China > Sichuan Province (0.28)
- Asia > China > Sichuan > Sichuan Basin (0.99)
- Asia > China > Qinshui Basin (0.99)
Fracture Pressure Prediction by Using the LSTM Neural Network Model
Ma, Tianshou (Southwest Petroleum University) | Zhang, Dongyang (Southwest Petroleum University) | Yang, Min (CCDC Drilling & Production Technology Research Institute, CNPC) | Liu, Yang (Southwest Petroleum University) | Liu, Wenming (Southwest Petroleum University) | Dang, Yufeng (Southwest Production Command Center)
ABSTRACT Fracture pressure plays a vital role in petroleum drilling and hydraulic fracturing. Currently, fracture pressure is mainly predicted through logging interpretation, but its calculation process is too complicated, and its accuracy needs to be further improved. Machine learning provides a new measure to address the above problems. Therefore, this paper aims to predict fracture pressure using the Long- and Short-Term Memory (LSTM) neural network method. The fracture pressure data set was generated by logging interpretation, then the nonlinear mapping relationship between logging parameters and fracture pressure was proposed using the LSTM model, and the mesh search method was used to optimize the hyperparameters of the LSTM model, so that the prediction of fracture pressure is realized. The results indicate that the in-situ stress state follows the normal faulting regime, i.e., vertical stress > maximum horizontal stress > minimum horizontal stress. Using the LSTM model with the optimal combination of hyperparameters, the prediction accuracy was significantly improved, and the root mean square error, mean absolute error, mean absolute percentage error, and coefficient of determination of the predicted fracture pressure were 0.304 MPa, 0.176 MPa, 0.209%, and 0.990, respectively. It is concluded that the LSTM model can effectively capture the variation trend of logging parameters with depth and the correlation information of logging parameters, which can realize the accurate prediction of fracture pressure. INTRODUCTION Fracture pressure is a very important fundamental engineering parameter that plays a critical role in oil drilling, completion and hydraulic fracturing (Chen et al. 2008; Fjar et al. 2008; Aadnoy and Looyeh 2011; Ma et al. 2017a). In drilling engineering, fracture pressure is the basis of drilling engineering design; if the fracture pressure is less than the effective wellbore pressure, the wellbore will experience tensile fracture (e.g., wellbore fracture or lost circulation), resulting in loss of drilling fluids. Predicting fracture pressure is therefore directly related to the safety of drilling operations. Incorrect or inaccurate prediction of fracture pressure can easily cause various drilling problems, such as lost circulation, induced well blowout, induced well collapse, and drill pipe sticking (Ma et al. 2017b).
- Asia > Middle East > Saudi Arabia (0.29)
- Asia > China > Sichuan Province (0.28)
- Oceania > New Zealand > North Island > Taranaki Basin > Mangahewa Field (0.99)
- Asia > China > Sichuan > Sichuan Basin (0.99)
Research Status and Prospect of Casing Deformation Mechanism and Control Methods in Shale Gas Wells in Sichuan Basin
Liu, Yang (Southwest Petroleum University ) | Tang, Qi (Southwest Petroleum University ) | Wu, Hao (Sichuan Shale Gas Exploration and Development Co., Ltd.) | Ma, Tianshou (Southwest Petroleum University)
ABSTRACT Casing deformation is a common problem of shale gas development in Sichuan Basin, which makes it difficult to run fracturing strings. It has become a bottleneck of restricting the development of shale gas resources. Through the investigation and the reference of many related documents, the main progress in the studies of casing deformation failure is summarized. The results show that many factors have influence on casing deformation, including the shear slip of fault or fracture evoked by hydraulic fracturing; the stress concentration in the vicinity of borehole caused by asymmetric fracturing; shale swelling caused by liquid phase invasion; annulus pressure build-up induced by the coupling effect of temperature and pressure, etc. Even so, the mechanical mechanism of casing deformation is still dominated by strain control and displacement control. Finally, the technical measures solving the problem of casing deformation are reviewed and discussed, raising casing rigidity, improving the displacement absorption capacity of cement sheath, optimizing fracturing parameters, adopting "temporary plugging fractures and multi cluster perforation" process, expansion tube technology and double layer casing technology, etc. It is hoped that this review can provide basic reference for further research and improvement of casing deformation control methods in shale gas well. INTRODUCTION Sichuan Basin is the earliest and the most successful area for shale gas exploration in China. Its exploitable shale gas reserves account for 30% of the whole country, and it contribute more than half of the total shale gas production. Sichuan Basin has become and will continue to be the main battleground for shale gas exploration and development in China (Zhang et al., 2021). However, compared with shale plays in North America region, the shale gas reservoir in Sichuan Basin has very different petrophysical and mechanical properties, and its geological complexity is much higher than that of the former. Meanwhile, the shale gas reservoir in the Sichuan Basin is buried more deeply at 2500โผ6500m, and the in-situ stress anisotropy is much more significant than that in North American region (He et al., 2022). These differences present many challenges to the effective development of shale gas in Sichuan Basin. Fortunately, the breakthroughs in horizontal drilling and multistage fracturing technology provide the possibility to address this question (Liu et al., 2017), but it also introduces several new problems. Casing deformation is one of the bottleneck problems in the shale gas industry. The reason is that the pressure and temperature of the casing change dramatically during the multistage fracturing process, which will result in a complex and extreme mechanical environment of the horizontal casing. According to statistics, the casing deformation rate of shale gas wells in some areas of Sichuan Basin is nearly 30% (Chen et al., 2021). Casing deformation in horizontal shale gas wells has many negative impacts on shale gas production, such as making it difficult to run bridge plugs and mill shoes or even unable to reach the intended depth, which increases non-productive time and significantly increases the cost of resource extraction. More seriously, if the deformation of the production casing becomes too severe, the fractured section will be abandoned, and the capacity of the shale gas well will be significantly reduced. Field measurement data shows that the production of wells with casing deformation is 27.3% lower than that of wells without casing deformation (Huang et al., 2020). As a result, the large number and frequency of casing deformation has become a major bottleneck restricting the development of shale gas in the Sichuan Basin, China. The problem of casing deformation has attracted extensive attention from many scholars, and a lot of research has been conducted. Scholars have put forward various hypotheses and theories on the mechanical mechanism of casing deformation, and have used various schemes and ideas to prevent and control casing deformation. Nevertheless, the casing deformation phenomenon has not been completely solved so far. For this purpose, this paper briefly reviewed the progress of studies on this aspect to provide the interesting information for casing deformation prevention and control.
- Research Report > New Finding (0.48)
- Research Report > Experimental Study (0.48)
- Asia > China > Sichuan > Sichuan Basin (0.99)
- North America > United States > Louisiana > China Field (0.95)
Data-Driven Models for Predicting Rate of Penetration Based on Machine Learning Algorithms
Liu, Yang (Southwest Petroleum University) | Xi, Yang (Southwest Petroleum University) | Xiang, Xingyun (Sinopec North China Petroleum Engineering Co., Ltd.) | Ma, Tianshou (Southwest Petroleum University) | Chen, Sitong (Southwest Petroleum University)
ABSTRACT Data-driven models are used extensively for predicting rate of penetration (ROP). However, what data-driven algorithm is best suited to ROP prediction is currently undecided. In this paper, the data-driven model based on back propagation neural network (BP-ANN) and random forest (RF) algorithms are proposed respectively to predict ROP. The features that include both the engineering and formation parameters are selected as the model inputs by combining physical drilling laws and correlation analysis. The optimal hyperparameter combinations of the model are found by cross-validation. The MAE, MSE and R are adopted as the indicators to evaluate the model performance. The case study illustrates how accurately and rapidly the data-driven model can be used to predict the ROP. The results indicate that the RF model can track the data-based ROPs more accurate even if hyperparameters optimization is ignored. The MAE, MSE and R of the optimized model are 0.243m/h, 1.599m/h, 0.989, respectively. While for the BP-ANN model, the predicted ROPs can achieve a more desired result after hyperparameters optimization, but it still cannot come close to the result of RF model. The present model provides some methodological bases for the further study on optimizing drilling parameters. INTRODUCTION Rate of penetration (ROP) is one of the key factors affecting drilling period and operating cost. Over the past few decades, researchers in drilling engineering field have been devoted to accurately predict and obtain an optimal value of ROP. Several physics-based models, e.g. the Maurer model (Maurer, 1962), the Warren model (Warren, 1987), the B-Y model (Bourgoyne and Young, 1974), the Hareland model (Hareland and Rampersad, 1994), the Detournay model (Detournay et al., 2008), the Motahhari model (Motahhari et al., 2010), are therefore proposed to predict ROP. All of these models take into account the engineering and geological factors to various extent, however, it still exists a great many limits in itself, especially in the extremely complex downhole environments. The primary reason is that the strong nonlinear relations between the ROP and the governing factors are not thoroughly understood (Zhang et al., 2022).
- North America (0.68)
- Asia > China > Sichuan Province (0.28)
- Asia > Middle East > Iran > Khuzestan > Zagros Basin > Marun Field (0.99)
- Asia > China > Sichuan > Sichuan Basin (0.99)