Cement Integrity Research Articles

Performance characterization of wellbore cement containing different CO2-resisting additives under geologic CO2 storage conditions

CO2 geological utilization and storage (CGUS) is an effective method for reducing greenhouse gas (GHG) emissions and mitigating their global warming effects. Wellbore cement is a crucial component of the CGUS system, but it exhibits chemical instability when exposed to CO2-rich environments, which can lead to potential CO2 leakage from wellbores. Maintaining the integrity of the wellbore cement is essential for preventing CO2 leakage, ensuring the long-term containment of CO2 in subsurface formations, and ensuring the success of CGUS projects. The objective of this study is to evaluate the impact of different CO2-resisting additives on the corrosion depth, compressive strength, and the pore structure of wellbore cement when exposed to CO2-saturated brine under geologic CO2 storage conditions. The mineralogy, microstructure, and morphology of specimens with different additives were analyzed using XRF, XRD, SEM and micro-CT. The results show that the cement containing supercritical CO2-modified Ca-montmorillonite (CM) was more effective in resisting CO2 corrosion than biochar (BC), crystalline admixture (CA), and geopolymer (GP). The corrosion inhibition efficiency, when compared to the reference sample (00-RF), followed the descending order of CM (44.04%), GP (26.17%), and BC (6.49%). Adding CA to the cement not only failed to inhibit corrosion but also increased the carbonation depth within the wellbore cement by 35.78%. The analysis of CM indicates that its reinforcement mechanisms stem from micro calcite-induced carbonate growth and montmorillonite swelling, and the prevention of CO2 infiltration is attributed to the structure of montmorillonite after supercritical CO2 modification. Regarding compressive strength, all samples with different additives exhibited a decline after CO2 corrosion. The sample containing supercritical CO2-modified CM showed the smallest reduction in compressive strength (10.40%) after carbonation while the sample with GP has the highest reduction (54.63%). In summary, compared to the other additives, CO2-modified montmorillonite has the most promising application prospect.

COMPARISON OF THE EFFECTS OF STANDARD NOZZLES AND EXTENSION TUBES ON THE EROSION OF PMMA USING PULSATING WATER JET TECHNOLOGY

The study of bone cement disintegration is important for advancing orthopedic and trauma surgery outcomes. Bone cement, commonly used in joint replacement procedures, plays a vital role in fixation implants. However, the long-term stability and integrity of bone cement are critical for the success of these procedures. This study focuses on the use of ultrasonic pulsating water jet technology for the selective removal of bone cement, aiming to provide a precise and efficient method for revision surgeries. The disintegration efficiency is measured in terms of depth, width and volume of the disintegrated bone cement as a result of variations in the nozzle geometry, supply pressure and traverse speed. Two different nozzle types, the standard nozzle insert and nozzle with an extension tube of 100 mm having a diameter of 0.3 mm, are used. Two supply pressure levels were taken as 10 and 20 MPa with five levels of traverse speeds as 0.5, 1, 1.5, 2 and 2.5 mm/s. The results showed an increased disintegration efficiency for all experimental conditions using an extension tube nozzle as compared to a standard nozzle (20 – 25% in terms of disintegration volume). Also, the disintegration efficiency increased with higher pressure level values (8.2 mm3 and 4.85 mm3 for p = 20 and 10 MPa, respectively) and lower traverse speed values. The results showed a promising direction in terms of the utilization of an ultrasonic pulsating jet with a modified nozzle type for higher bone cement disintegration efficiency.

Influence of Natural Dentin Biomodification Agent on Push-Out Bond Strength and Nanoleakage of Self-Adhesive Resin Cement Luting of Glass-Fiber Posts.

To evaluate the plant-derived compound lignin (LIG) as a pretreatment of intraradicular dentin in combination with EDTA on push-out bond strength (PBS) and nanoleakage of the glass fiber posts (GFPs) cemented using adhesive resin cement. Twenty-eight human incisor roots were prepared for GFP cementation and divided based on dentin pretreatment: (1) CONTROL: no pretreatment, (2) EDTA: 17% EDTA for 3 min, (3) EDTA-LIG: 17% EDTA and 2% lignin for 3 min, (4) EDTA-PAC: 17% EDTA and 2% lignin for 3 min. The GFPs were cemented using the self-adhesive resin cement Multilink Speed. The roots (n = 7) were sectioned into 1 mm-thick discs and subjected to PBS testing after 1 week or 6 months. Nanoleakage was analyzed by SEM. Statistical analysis was performed using two-factor ANOVA and Tukey's test (p < 0.05). Higher PBS was identified for the CONTROL group (p < 0.001). After 6 months, the EDTA-LIG maintained the bond strength with a predominance of mixed failures, while the EDTA-PAC, EDTA, and CONTROL groups showed reduction of bond strength, with a predominance of adhesive failures along with severe silver infiltration in the interface. LIG associated with EDTA as a pretreatment for intraradicular dentin shows significant potential for attaining stable bond strength and interfacial integrity of self-adhesive resin cement to intraradicular dentin.

Development and Evaluation of Insulation Materials for Deepwater Cementing.

Marine oil and gas resources are abundant in deepwater regions, where the shallow seabed harbors natural gas hydrate layers due to the cold temperature and high-pressure environment. Hydrates are prone to thermal decomposition, which can compromise the integrity of cement sealing and even lead to accidents like blowouts. While current low-hydrated heat cement systems mitigate hydrate decomposition from cement hydration heat during the waiting period for cementing, they do not address heat transfer from deep strata to shallow hydrate layers through fluid circulation in the tubing during deep oil and gas development. Rather than utilizing costly pipe insulation technology, adjusting the thermal conductivity of well cement emerges as a cost-effective approach to prevent heat loss in the wellbore to the hydrate layer and thus inhibit hydrate decomposition. The critical aspect lies in utilizing insulation functional materials. This study delves into the functional and structural design of insulation materials suitable for cement slurry systems in well cementing, outlining the preparation methods and processes for two insulation materials (SDBW and SDBW-II) tailored for deepwater well cementing. SDBW and SDBW-II are both nuclear shell structural materials. The core is made of high-strength hollow microspheres, produced by using a reverse suspension polymerization method to form spheres followed by high-temperature sintering. The shell consists of a wear-resistant BPA epoxy resin layer, with the surface of SDBW-II also containing highly reflective glass microspheres. Incorporating 20% of material SDBW into the cement reduces the thermal conductivity of the cement stone from 0.8 to 0.31 W·(m·K)-1 while achieving a compressive strength of 6 MPa after 24 h at 20 °C. Material SDBW-II offers both thermal resistance and reflection functions, increasing reflectivity (R) from 0.3 to 0.5. By adding 20% of this material to the cement, under the same conditions, although the compressive strength decreases to 4.2 MPa, the thermal conductivity can be reduced to 0.27 W·(m·K)-1. Furthermore, there is no significant change within 180 days, demonstrating long-term thermal insulation stability. These developed insulation materials can effectively improve the thermal insulation performance of the cement sheath, thereby maintaining the stability of the upper natural gas hydrate layer in the oil and gas production process of deepwater wells, providing an innovative solution for the long-term operation of deepwater oil and gas wells.

Corrosion Characteristics of Polymer-Modified Oil Well Cement-Based Composite Materials in Geological Environment Containing Carbon Dioxide.

Oil well cement is easily damaged by carbon dioxide (CO2) corrosion, and the corrosion of oil well cement is affected by many factors in complex environments. The anti-corrosion performance of oil well cement can be improved by polymer materials. In order to explore the influence of different corrosion factors on the corrosion depth of polymer-modified oil well cement, the influence of different corrosion factors on corrosion depth was studied based on the Box-Behnken experimental design. The interaction of different influencing factors and the influence of multiple corrosion depths were analyzed based on the response surface method, and a response surface model was obtained for each factor and corrosion depth. The results indicate that within the scope of the study, the corrosion depth of polymer-modified oil well cement was most affected by time. The effects of temperature and the pressure of CO2 decreased sequentially. The response surface model had good significance, with a determination coefficient of 0.9907. The corrosion depth was most affected by the interaction between corrosion time and the pressure of CO2, while the corrosion depth was less affected by the interaction between corrosion temperature and corrosion time. Improving the CO2 intrusion resistance of cement slurry in an environment with a high concentration of CO2 gas can effectively ensure the long-term structural integrity of cement.

Transfer learning for acoustic cement bond evaluation: An image classification approach using acoustic variable Density log

Ensuring the integrity of wellbore cement is critical for the environmental protection, safety, and economic viability of oil, gas, geothermal, and Carbon Capture and Storage (CCS) operations. Acoustic logging is the most commonly used evaluation method, and interpreting its data requires significant expertise, often informs high-stakes decisions. Machine Learning (ML) has been used to help the data interpretation, but they are heavily reliant on meticulous feature engineering—a labor-intensive and expertise-driven task. Moreover, ML methods cannot tell which portions of input acoustic data are most important in the cement evaluation task. This level of analysis is vital, as it can significantly inform and improve future strategies for acoustic logging data collection and signal processing, ultimately improving the cement evaluation results. To address these challenges, we present a generalized workflow. First, we convert Variable Density Log (VDL) data into images using the Continuous Wavelet Transform (CWT). Then, we apply transfer learning for image classification to enhance the classification of wellbore cement isolation. In transfer learning stage, the images are processed using several pre-trained image classifiers—Xception, VGG16, MobileNetV2, and ResNet50—originally trained on the extensive ImageNet database containing over 14 million images. To adapt these models for our specific task, we added a global average pooling layer to reduce feature map dimensionality, followed by a fully connected layer with a Rectified Linear Unit (ReLU) activation function to introduce non-linearity and enhance learning capability. We replaced the original final layer of each classifier with a new three-neuron layer using softmax activation, tailored for multi-class classification. We preserved the general characteristics learned from the ImageNet dataset by freezing all original layers except for the newly added ones and compiled the models using the Adam optimizer. The performance of these adapted models was evaluated based on accuracy, loss, and F1 score. We applied this workflow to two distinct datasets: the first from a Norwegian wellbore and the second from a hydrocarbon well in China. In the Norwegian case, the Xception model achieved a classification accuracy of 97.4%, which was further refined to 99.0% through the implementation of Gradient-weighted Class Activation Mapping (Grad-CAM), revealing critical frequency ranges that traditional ML methods could not identify. In the Chinese case, employing the same models and workflow, the MobileNetV2 algorithm demonstrated exceptional performance, achieving a 99.6% accuracy in predicting cement isolation. In addition to achieving high accuracy, our results reveal that the VDL frequency content between 20 and 25 kHz is more critical for cement evaluation in the investigated wells than other frequency ranges, a level of analysis unattainable with traditional ML methods. Furthermore, our approach eliminates the need for deep knowledge in feature engineering, typically requisite in traditional ML, and operates effectively without any feature engineering. These results underscore the efficacy of our approach across diverse geological settings and highlight the potential of transfer learning to revolutionize cement evaluation automation, inspiring its broader application in the industry.

HOG-CNN based evaluation of cement integrity using 2D dispersion curves from an experimental through tubing logging setup

In oil wells, adequate cementation is essential to guarantee that the well has support for the casing and is able to isolate the well from groundwater. Operations known as Plugging & Abandonment (P&A) must carry out inspections in the cement layer of the well to ensure that the bond quality of the cement with the formation and the hydraulic isolation is adequate before well sealing. The interpretation of data logs during the decommissioning processes is made exclusively for a petrophysicists team, which makes the process susceptible to human errors. Furthermore, it requires a lot of analysis time, increasing the search for alternative solutions that help reduce errors in the interpretation of data logs. So far, the use of machine learning has proven to be a strong candidate in this search. This paper deals with frequency domain images (dispersion curves and Cepstrum) that are acquired from acoustic pressure signals obtained in the time domain and along the vertical axis of an experimental setup. These images are used to train machine learning models to test and compare the accuracies obtained. An adjustment of the hyperparameters was carried out to find those that best describe the simulated experimental characteristics. Furthermore, the convolution neural network (CNN) model was combined with the oriented gradient histogram technique (HOG) to verify its efficiency by analyzing experimental data. Two different databases were used in this work, one with 130 samples relating to the average results of the four hydrophones used in the experiment and one with 520 samples relating to all results. The results found demonstrated that when using the dispersion curves as input with the CNN the accuracy hits 100%. Other combinations of models were also tested hitting similar results. This article contributes to the current research scenario as it presents an innovative combination of machine learning techniques applied to the oil and gas field (HOG-CNN) with the proposal to compare different types of databases, such as using Cepstrum instead of dispersion curves and image processing.

Debulking of the Femoral Stem in a Primary Total Hip Joint Replacement: A Novel Method to Reduce Stress Shielding.

In current-generation designs of total primary hip joint replacement, the prostheses are fabricated from alloys. The modulus of elasticity of the alloy is substantially higher than that of the surrounding bone. This discrepancy plays a role in a phenomenon known as stress shielding, in which the bone bears a reduced proportion of the applied load. Stress shielding has been implicated in aseptic loosening of the implant which, in turn, results in reduction in the in vivo life of the implant. Rigid implants shield surrounding bone from mechanical loading, and the reduction in skeletal stress necessary to maintain bone mass and density results in accelerated bone loss, the forerunner to implant loosening. Femoral stems of various geometries and surface modifications, materials and material distributions, and porous structures have been investigated to achieve mechanical properties of stems closer to those of bone to mitigate stress shielding. For improved load transfer from implant to femur, the proposed study investigated a strategic debulking effort to impart controlled flexibility while retaining sufficient strength and endurance properties. Using an iterative design process, debulked configurations based on an internal skeletal truss framework were evaluated using finite element analysis. The implant models analyzed were solid; hollow, with a proximal hollowed stem; FB-2A, with thin, curved trusses extending from the central spine; and FB-3B and FB-3C, with thick, flat trusses extending from the central spine in a balanced-truss and a hemi-truss configuration, respectively. As outlined in the International Organization for Standardization (ISO) 7206 standards, implants were offset in natural femur for evaluation of load distribution or potted in testing cylinders for fatigue testing. The commonality across all debulked designs was the minimization of proximal stress shielding compared to conventional solid implants. Stem topography can influence performance, and the truss implants with or without the calcar collar were evaluated. Load sharing was equally effective irrespective of the collar; however, the collar was critical to reducing the stresses in the implant. Whether bonded directly to bone or cemented in the femur, the truss stem was effective at limiting stress shielding. However, a localized increase in maximum principal stress at the proximal lateral junction could adversely affect cement integrity. The controlled accommodation of deformation of the implant wall contributes to the load sharing capability of the truss implant, and for a superior biomechanical performance, the collared stem should be implanted in interference fit. Considering the results of all implant designs, the truss implant model FB-3C was the best model.

Hydrogen Impact on Cement Integrity during Underground Hydrogen Storage: A Minireview and Future Outlook

Hydrogen Impact on Cement Integrity during Underground Hydrogen Storage: A Minireview and Future Outlook

Engineered Materials, Machine Learning Enhance Carbon Storage Well Integrity

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 214844, “Engineered Materials and Machine Learning for Carbon Storage Well Integrity,” by Jacob Pollock, Oceanit Laboratories, and Hani Elshahawi, SPE, NoviDigiTech. The paper has not been peer reviewed. _ The success of CO2 injection operations, and the endurance of long-term storage, are partially dependent on well design and the materials used for well construction. The authors describe a stack of technologies they have developed that enable enhanced well robustness, monitoring of carbon-storage facilities, and modeling of their performance. The combination of these technologies enables the tracking of downhole and subsurface fluid distribution and flow. Furthermore, the scalable technologies can be used to exploit remaining reservoirs while preventing CO2-plume migration. Introduction Besides site selection and geological features that influence plume migration, well-construction design and materials have a major effect on successful storage. Injection wells are drilled into the storage site and completed with multiple cemented casing strings, with access to the reservoir through perforations or gravel packs. Cement supports and protects the metal casings from corrosive fluids while isolating the storage reservoir from freshwater aquifers by sealing off the wellbore annulus (Fig. 1). Cement integrity and durability are critical to successful carbon capture, storage, and use (CCUS) operations. Despite their importance, current cement-evaluation methods suffer from limited resolution, poor discrimination, and ambiguous interpretation. The authors have developed steel/cement interfacial bonding nanotechnology that enhances both mechanical bonding and acoustic coupling, along with acoustic metamaterials for sensing cement and tracking particles. The acoustic band gap of the materials was demonstrated to improve acoustic contrast and provide information about the cement environment based on frequency and amplitude. Furthermore, data-processing and machine-learning methods have been developed to interpret subsurface readings with more accuracy and deeper insight. Neural networks can be used to interpret the results of smart material detection and sensing, providing new information that was previously unattainable. Engineered Materials for Well Construction New classes of construction components with enhanced properties may be self-healing or passively sensing or may have outstanding physical properties such as mechanical strength. Nanoscale treatments can alter the surface characteristics of materials, endowing them with engineered interfacial behavior. Passive-sensing materials can alter incoming energy waves that can be detected to discern information about material condition and environment. These technologies can improve the properties of well-construction materials for carbon storage, increasing integrity and allowing monitoring of well and reservoir states. The results of successful laboratory and field trials of each technology described in this section are provided in the complete paper.

Experimental evaluation of cement integrity on exposure to supercritical CO2 using NMR: Application to geostorage

Carbon sequestration is one approach to achieve carbon dioxide reduction in the atmosphere. Underground storage of CO2 requires an understanding of geochemical and geomechanical alteration on the integrity of the injection wellbore. In this study, we investigate the reactivity of supercritical CO2 (scCO2) at 65 °C and 20.7 MPa on Portland class G cement plugs used for oil and gas well completion, for exposure of up to 5 weeks.For nanoporous media, such as cement, diffusion is believed to be the major mass transport mechanism (Perkins and Johnston, 1963) [1]. To quantify the extent of the alteration (mineralization/dissolution) on fluid diffusivity through the cement matrix, a novel approach based on Nuclear Magnetic Resonance (NMR) is employed to derive diffusional tortuosity. Comparing pre- and post-scCO2 exposure, deuterium oxide (D2O) intrusion profiles allow us to determine flow path alteration in the cement plugs. Additional characterizations include Fourier Transform Infrared Spectroscopy (FTIR) to observe the change in cement composition, micro X-ray Computed Tomography (μXCT), along with Scanning Electron Microscopy (SEM) and Energy Dispersive Spectroscopy (EDS) to determine invasion extent and microstructure modifications, Mercury Injection Capillary Pressure (MICP) for pore throat size distribution and BET N2 isothermal adsorption for surface area and pore size distribution.The results show that exposure to scCO2 promotes both calcium carbonate precipitation and dissolution simultaneously. However, the alteration is pore size dependent. After 5 weeks of exposure, there is evidence of carbonate dissolution in smaller pores (<30 nm) and both precipitation and dissolution in larger pores (30–200 nm). The alteration of the cement plugs leads to a decrease in the storage and connectivity of the cement. The porosity decreased from 37 to 33 % in 5 weeks, while the matrix tortuosity increased by 6 and 3 times after 2 and 5 weeks of exposure, respectively. The experimental results imply that the cement carbonate precipitation can limit the migration of scCO2 through the cement matrix.This work also highlights an alternative laboratory approach to quantify the risk associated with scCO2 exposure on Portland cement using NMR-derived tortuosity.

PEEK surface treatment on surface roughness and bond integrity to composite resin utilizing Er: YAG, Rosebengal activated by PDT, and aluminum trioxide particles

AimsTo evaluate the impact of conditioning protocols, aluminum trioxide (Al2O3), Er:YAG laser (EYL), and Rosebengal (RB), on the surface roughness (Ra) and shear bond strength (SBS) of polyetheretherketone (PEEK) attached to composite restorations. MethodEighty PEEK discs in total were produced and then divided into four groups (n = 20). Group1:Sulfuric acid (SA), Group 2: PDT (RB), Group 3: Al2O3, Group 4 EYL, respectively. The Ra of PEEK discs was evaluated using the surface profilometer. After being luted, the discs were attached to composite resin discs. After that, samples were put to SBS testing on a Universal testing apparatus. A stereo microscope was also used to evaluate the type of breakdown. The data were analyzed using Tukey's test and one-way analysis of variance. ResultsThe SA treated group exhibited the highest Ra. Nevertheless, the RB specimens activated by PDT treatment had the lowest mean Ra score. The group that received the treatment of SA exhibited the highest average score of SBS. In contrast, specimens treated with PDT and activated by RB exhibited the lowest levels of bond fidelity. Cohesive failure emerges as the prevailing kind of fracture within the various groups subjected to testing. ConclusionThe utilization of Al2O3, RB activated by PDT, and EYL shows promise as a viable substitute for Sulfuric acid in enhancing the bond integrity of composite cement and surface roughness in PEEK materials

Research Status and Development Prospect of Wellbore Integrity in China

Summary As the exploration and development of oil and gas move into increasingly challenging locations and harsher environments, well integrity becomes more difficult to maintain. High temperatures, pressures, and corrosion can all contribute to wellbore integrity failure. Such failures can have significant financial and environmental consequences, including gas leakage and fluid spills. In this paper, we review the development and technical advancements of wellbore integrity research both in China and abroad and look forward to the development direction of wellbore integrity in China. We provide basic background knowledge for those interested in wellbore integrity and also share the progress and development direction of integrity research for wellbore integrity researchers. Through research and analysis, some conclusions can be drawn. Countries around the world are actively studying wellbore integrity and have developed a large number of standards, especially the United States and Norway, which have the most standards. The most common way to analyze wellbore integrity is to first divide the entire wellbore into different wellbore barrier units according to different standards, such as ISO 16530-1, and then study risk factors and integrity management measures in different units. Mainstream research is mostly carried out around the integrity of casing, cement, and tubing, and many achievements have been made, but the study of packer and downhole safety valve is still on the way. Wellbore integrity risk assessment aims to quantify potential risks and establish risk levels to support decision-making for on-site wellbore integrity control. This is achieved by identifying factors affecting wellbore integrity, establishing an evaluation index system and processing evaluation indicators to determine failure probability and impact consequences. The resulting risk value can be divided into different areas using the “as low as reasonably practicable principle” or a risk matrix graph. However, due to the complexity of the factors involved and the subjectivity of risk classification rules, there are still challenges in promoting the evaluation model and reducing errors in the evaluation results. China should actively promote interdisciplinary integration and respond to the call for “dual carbon goals” to break through the current bottleneck in wellbore integrity research. This can be achieved by promoting the development of quantitative wellbore integrity risk assessment methods, developing supporting evaluation software based on big data, and by tackling the integrity challenges faced by different types of wells and promoting the development of wellbore integrity discipline.

Investigation of the hydraulic integrity of cement plug: Oilwell cementitious materials

The loss of hydraulic integrity in oil and gas wells due to the loss of cement sheath sealability can lead to environmental contamination, annular pressure build-up, and safety threats. In this study, we examine the hydraulic integrity of geopolymers an alternative to cement to be used in well cementing. The hydraulic integrity of geopolymer was compared to conventional API class G and Industrial expansive cement. Down-scaled test specimens representing cement-plug in casing were prepared and tested using an in-house experimental set-up that allows continuous curing and testing of the cementitious materials under undisturbed pressure and temperature conditions. The samples were cured at 90 °C and 172 bar for 7 days after which the hydraulic sealability of the specimens was examined by applying a pressure differential to one end of the specimen and observing the resulting fluid leakage rates on the other end. The leakage rates were then expressed in terms of permeability and microannuli aperture. By injecting nitrogen and water, it was possible to compare the effects of fluid type on the hydraulic sealability of cementitious materials. Lastly, we examined the hypothesis of a linear relationship between plug length and its hydraulic sealability. The results indicate that geopolymer and Industrial expansive cement have higher hydraulic sealability compared to API class G. Geopolymers also have sufficient hydraulic bond strength to perform as much as Industrial expansive cement. The fluid type used in testing does not play a critical role in the loss of hydraulic sealability of cementitious materials. The influence of cement plug length showed varying trends on the hydraulic sealability of the cementitious materials. The results presented in this work help us understand the sealing potential of cementitious materials and the need for standards for performing laboratory-scale hydraulic sealability tests. This can benefit the improvement of cement integrity tests and well abandonment operations.

Research on the Relationship between Pore Structure and the Compressive Strength of Oil-Well Cement

The integrity of wellbore cement is an important guarantee for the long-term safety and effectiveness of carbon dioxide geological storage. During the process of CO2 capture, utilization, and storage, construction factors will cause changes in temperature and pressure distribution, leading to changes in the pore structure of cement and a decline in compressive strength, which can easily cause the failure of cement ring integrity. To provide theoretical guidance and analysis methods for evaluating the mechanism of cement strength performance degradation and optimizing injection parameters, in this study, we conducted the following research based on relevant studies: (1) The fracture theory was revised based on the characteristic factors of oil-well cement; (2) a pore structure model was established to analyze the failure process of cement, clarifying the relationship between pore structure and the compressive strength of cement; (3) the parameters of the pore structure model were determined and analyzed, considering the influence of cement content and total porosity on the model, and finally, the regression parameter K value was determined to be 1600. This article can provide a useful reference for the research on the failure of cement rings in the CO2 injection process and other related studies.

Geochemical Integrity of Wellbore Cements during Geological Hydrogen Storage.

Increasing greenhouse gas emissions have put pressure on global economies to adopt strategies for climate-change mitigation. Large-scale geological hydrogen storage in salt caverns and porous rocks has the potential to achieve sustainable energy storage, contributing to the development of a low-carbon economy. During geological storage, hydrogen is injected and extracted through cemented and cased wells. In this context, well integrity and leakage risk must be assessed through in-depth investigations of the hydrogen-cement-rock physical and geochemical processes. There are significant scientific knowledge gaps pertaining to hydrogen-cement interactions, where chemical reactions among hydrogen, in situ reservoir fluids, and cement could degrade the well cement and put the integrity of the storage system at risk. Results from laboratory batch reaction experiments concerning the influence of hydrogen on cement samples under simulated reservoir conditions of North Sea fields, including temperature, pressure, and salinity, provided valuable insights into the integrity of cement for geological hydrogen storage. This work shows that, under the experimental conditions, hydrogen does not induce geochemical or structural alterations to the tested wellbore cements, a promising finding for secure hydrogen subsurface storage.

On hydrogen-cement reaction: Investigation on well integrity during underground hydrogen storage

Underground hydrogen storage (UHS) is becoming a promising technology to help achieve full hydrogen economy and support the energy transition to carbon net-zero. One of the important parameters for securing UHS for example in depleted gas reservoirs is related to the wellbore integrity and cement seal, which is rarely addressed. When hydrogen is injected, it can react with the cement around the wellbore, and cause various alterations in cement petro-physical properties. Therefore, it is crucial to understand the associated reactions between hydrogen and cement and their implications for cement degradation. In this study, hydrogen injection experiments were performed on two cement core plugs (class G) under 1400 psi and 75 °C for 125 days, and the impact on cement integrity was evaluated. The results show low reactivity of hydrogen with cement and minor alteration in the petro-physical properties of the cement samples. The XRD results show a minor increase in Alite contents after hydrogen injection, while the observed calcite growth was attributed to the cement hydration process. Despite the presence of high mobility elements such as Ca, Mg, K and Al in the cement plugs, the minor redox reactions between cement minerals and hydrogen inhibit the precipitation of high-density minerals. However, we indeed observed for the first time an increase in cement weight and density with hydrogen injection, which suggest that hydrogen/brine injection may promote the precipitation of high density products. This caused a reduction in the CT porosity by 8.86% and 8.43% in samples C#1 and C#2 respectively. However, the total reduction in porosity is considered minor, suggesting a limited impact on cement integrity -which is favorable for UHS-. Furthermore, the alteration in the statistical distributions of P- and S-waves caused a minor increase in Poisson's ratio and dynamic elastic modulus (E), suggesting a low risk of wellbore cement degradation during UHS. The obtained results provide clear analyses of the reactivity of cement to hydrogen injection, and suggest that no significant impact on wellbore integrity or cement seal would be expected during UHS.

Coupled experimental assessment and machine learning prediction of mechanical integrity of MICP and cement paste as underground plugging materials

Compromised integrity of cementitious materials can lead to potential geo-hazards such as detrimental fluid flow to the wellbore (borehole), potential leakage of underground stored fluids, contamination of water aquifers, and other issues that could impact environmental sustainability during underground construction operations. The mechanical integrity of wellbore cementitious materials is critical to prevent wellbore failure and leakages, and thus, it is imperative to understand and predict the integrity of oilwell cement (OWC) and microbial-induced calcite precipitation (MICP) to maintain wellbore integrity and ensure zonal isolation at depth. Here, we investigated the mechanical integrity of two cementitious materials (MICP and OWC), and assessed their potential for plugging leakages around the wellbore. Further, we applied Machine Learning (ML) models to upscale and predict near-wellbore mechanical integrity at macro-scale by adopting two ML algorithms, Artificial Neural Network (ANN) and Random Forest (RF), using 100 datasets (containing 100 observations). Fractured portions of rock specimens were treated with MICP and OWC, respectively, and their resultant mechanical integrity (unconfined compressive strength, UCS; fracture toughness, Ks) were evaluated using experimental mechanical tests and ML models. The experimental results showed that although OWC (average UCS = 97 MPa, Ks = 4.3 MPa·√m) has higher mechanical integrity over MICP (average UCS = 86 MPa, Ks = 3.6 MPa·√m), the MICP showed an edge over OWC in sealing microfractures and micro-leakage pathways. Also, the OWC can provide a greater near-wellbore seal than MICP for casing-cement or cement-formation delamination with relatively greater mechanical integrity. The results show that the degree of correlation between the mechanical integrity obtained from lab tests and the ML predictions is high. The best ML algorithm to predict the macro-scale mechanical integrity of a MICP-cemented specimen is the RF model (R2 for UCS = 0.9738 and Ks = 0.9988; MAE for UCS = 1.04 MPa and Ks = 0.02 MPa·√m). Similarly, for OWC-cemented specimen, the best ML algorithm to predict their macro-scale mechanical integrity is the RF model (R2 for UCS = 0.9984 and Ks = 0.9996; MAE for UCS = 0.5 MPa and Ks = 0.01 MPa·√m). This study provides insights into the potential of MICP and OWC as near-wellbore cementitious materials and the applicability of ML model for evaluating and predicting the mechanical integrity of cementitious materials used in near-wellbore to achieve efficient geo-hazard mitigation and environmental protection in engineering and underground operations.

Machine learning-based cement integrity evaluation with a through-tubing logging experimental setup

Assessing the integrity of the cement layer and the quality of its bond to the casing and formation is paramount to ensure that the wellbore is hydraulically isolated from the surrounding environment before permanently sealing the well. Such inspection is part of Plugging & Abandonment (P&A) operations, and it is usually achieved through well logging tools, which provide a vast amount of data that a skilled specialist interprets. The process is human-dependent, error-prone, and time-consuming. There has been an increasing interest in solutions that allow an automatic interpretation of the logging data since the recent panorama of the oil and gas industry indicates a growing P&A demand. Such solutions aim at reducing the dependence on human knowledge and consequently increasing the reliability and accuracy of the cement integrity evaluation. Therefore, this work presents an experimental setup capable of emulating defective cement layer configurations of real-world oil wells in single or multi-string arrangements. Such flexibility enables acquiring logging data for multiple well conditions and building a rich logging database to develop a supervised learning framework and define the most suitable model for performing the cement integrity evaluation. Several logging runs were performed, producing a database with 130 samples, including varied tubing eccentricity levels and cement layer conditions. A complete analysis of the data both in the time domain as well as in the frequency–wavenumber domain was performed, highlighting the complexity of the interpretation task. A resampling-based workflow was employed to evaluate machine learning models of different families. The models were tested under three scenarios, and accuracy and computational complexity metrics were computed to compare their performance. The results showed that shallow learning models can perform satisfactorily well even with less data available for training. The support vector machine stood out, achieving a mean accuracy score higher than 0.99 while being able to predict the cement sheath’s condition in less than 1 ms. This paper contributes to the research on the cement integrity evaluation by presenting a study that combines an experimental setup mimicking several oil well conditions and the employment of machine learning as a diagnostic tool, which has no precedents in recent literature regarding the acoustic logging knowledge field.

Technology Focus: Cementing and Zonal Isolation (May 2023)

In 2022, the topics of the cementing and zonal isolation papers published were generally similar to those presented in previous years. A noticeable departure from previous years, however, was that many of the authors emphasized that their work would result in a reduction of greenhouse-gas emissions. The approaches taken to reduce emissions can be broadly split into three categories: improving operational efficiency, increasing the reliability of zonal isolation (primary cementing, annulus leak repair, and plug sealing), and reducing the CO2 footprint of sealing materials. Work to improve operational efficiency and increase the reliability of zonal isolation has been ongoing since the start of well construction as general good practice to improve safety and hydrocarbon recovery and reduce costs. The efficiency and reliability improvements, however, have not regularly been promoted as reducing the environmental impact, except for cases of leak repair. Reduction of the CO2 footprint of sealing materials is a growing source of research and development activity and subsequent publication. During the past year, 13% of the cementing and zonal isolation papers published covered work on the development of geopolymer systems. Although work to develop geopolymer systems for zonal isolation has been ongoing for more than 15 years, no case histories have been published to date. The long development time is not surprising because any new system will have to be at least as reliable as the current Portland-cement-based systems; otherwise, the overall environmental impact may be worse, with more repairs or less-efficient processes offsetting the reduced CO2 footprint of the sealant. Geopolymers are not the only option to replace Portland-cement-based systems for primary cementing, and the evaluation of alternate sealant systems is certainly not new (see paper SPE-508-G from 1956). Is it time to revisit previous work in light of new environmental constraints? Recommended additional reading at OnePetro: www.onepetro.org. IPTC 22019 Enhancing Slurry Pumping Efficiency, Improving Cement Coverage, and Ensuring Zonal Isolation With Temperature-Triggered Antisettling Technology by Xiangyu Liu, ChampionX, et al. SPE 210639 Thermodynamic Modeling on Wellbore Cement Integrity During Underground Hydrogen Storage in Depleted Gas Reservoirs by Lingping Zeng, Curtin University, et al. OTC 31562 Cementing the First Australian Offshore Carbon Capture and Storage Appraisal Well by Ariel Lyons, SLB, et al.