Casing Collapse Research Articles

Non-universality and dissipative anomaly in compressible magnetohydrodynamic turbulence

We systematically study the dissipative anomaly in compressible magnetohydrodynamic (MHD) turbulence using direct numerical simulations, and show that the total dissipation remains finite as viscosity diminishes. The dimensionless dissipation rate $\mathcal {C}_{\varepsilon }$ fits well with the model $\mathcal {C}_{\varepsilon } = \mathcal {C}_{\varepsilon,\infty } + \mathcal {D}/R_L^-$ for all levels of flow compressibility considered here, where $R_L^-$ is the generalized large-scale Reynolds number. The asymptotic value $\mathcal {C}_{\varepsilon,\infty }$ describes the total energy transfer flux, and decreases with increase of the flow compressibility, indicating non-universality of the dimensionless dissipation rate in compressible MHD turbulence. After introducing an empirically modified dissipation rate, the data from compressible cases collapse to a form similar to the incompressible MHD case depending only on the modified Reynolds number.

Study on transient prediction method of dynamic underbalanced pressure after perforation detonation in ultra-deep wells

Dynamic underbalanced pressure creates a significant transient pressure difference between the upper and lower ends of the packer and the inner and outer walls of the string below the packer, which can lead to the failure of the packer, the tubing, and the casing and is one of the main reasons for the low success rate of the perforation-acidizing-testing combined technology in ultra-deep wells. A danger caused by the dynamic underbalanced pressure is increased rapidly with an increase in the well depth. Despite the fact that researchers have a well enough understanding of the applications and benefits of the dynamic underbalanced pressure, the mechanism of the wellbore failure caused by the dynamic underbalanced pressure is inadequate. Therefore, a pressure drop model of tubing-casing annulus fluid is established, and a seepage model of reservoir rock is given. A transient prediction method of the dynamic underbalanced pressure is developed by coupling the pressure drop model and the seepage model. Then, the determining factors, key nodes of the maximum value, and derivation and propagation laws of the dynamic underbalanced pressure are revealed. An influence study focusing on an ultra-deep well is conducted. The obtained results indicated that the dynamic underbalanced pressure describes a fast drop in the annulus fluid pressure caused by the fluid flow among the annulus, the perforating guns, and the perforation tunnels since the pressures in the perforating guns and the perforation tunnels are lower than the annulus pressure after the perforation detonation. The annulus fluid pressure can slowly recover and increase due to the fluid flow between the screens and the annulus and the fluid flow between the reservoir rock and the wellbore. The main form of the wellbore failure caused by the dynamic underbalanced pressure is the casing collapse deformation. Therefore, changing perforating conditions, wellbore conditions, and reservoir rock conditions can increase the maximum for the dynamic underbalanced pressure to improve the success rate of the combined technology. The research presented in this paper can provide a new understanding and prediction method of the dynamic underbalanced pressure.

Influence of the scour phenomenon on the degradation of structures: the case of bridges in Algeria

The scouring of river piles has been the main historical cause of damage and destruction of bridges over the past centuries. Today, the situation is better throughout the world due to modern techniques for carrying out work in the river (foundation work) and the ability to carry out long-distance work, reducing the number of piers in the river. But the scouring of bridge piers remains one of the most frequently recorded degradations in our country. Scouring of bridge piers is a serious issue that can threaten the stability of a bridge. It refers to the erosion of sediment (think sand, gravel, rock) around the base of a bridge pier caused by flowing water. Scour holes can undermine the foundation of the pier and expose the foundation of the pier, reducing its ability to support the weight of the bridge. This can lead to cracks in the pier itself, or even complete collapse in severe cases. On the other hand, scour is the erosion of soil around a bridge pier by flowing water. It's a major concern for bridge safety in Algeria, especially as many bridges were built before stricter seismic codes were introduced in 2010. Scour can weaken the foundation of a bridge pier, making it more susceptible to collapse during earthquakes or floods. The aim of this work is to try to study the phenomenon from different angles in order to clearly define the problem in the Algerian context, based on the analysis of several cases of work subject to scouring.

Casing Collapse and Salt Creeping for an Iraqi Oil Field: Implications for Mitigation

Casing collapse is considered one of the costliest problems that occurs in the oil industry, and it happens when the stresses or loads exceed the casing collapse resistance or due to casing wear and corrosion or salt creeping. For X oil field, located in Iraq's southern east, a casing collapse phenomenon has been exposed in four wells, including well X-1, and the salt creeping may be the main reason because the collapsed casing section is encountered by a salt formation that may be creeping under compression. In this paper, Lower-Fars’s formation had been specified as the high-pressure salt formation that causes this problem according to the analysis of the provided data that included the depths of the collapse, log data and the final geological report. A new suggested casing design had been suggested by using pore pressure, fracture pressure, and horizontal stresses that were estimated by interactive petrophysics software from the well log data. The proposed and current casing designs were Simulated using Landmark-stress check software, and the proposed casing design indicates changing the grade from (L-80, 47 ppf) to (N-80, 53 ppf), which prevents the problem from recurring when drilling new wells in the same field as well as the proposed casing design can be economically considered feasible.

Long, short, and mediumterms wind speed prediction model based on LSTM optimized by improved moth flame optimization algorithm.

Time series prediction of wind speed has been widely used in wind power generation. The volatility and instability of wind speed have a large negative impact on wind turbines and power systems, which can lead to grid collapse in severe cases. Therefore, accurate wind speed prediction is crucial for wind power generation. In this paper, considering the influence of different parameters on algorithm training and prediction, an improved moth flame optimization algorithm is constructed to optimize the LSTM wind energy prediction system to obtain better performance. The system consists of three modules: data preprocessing, optimization, and prediction. The data preprocessing module uses fuzzy information granulation to blur the input data. On this basis, the combination of swarm intelligent optimization algorithm and prediction model can effectively predict wind speed time series. Taking the California wind farm as an example, the MAPE of the experiment in the short-term forecast is 3.15%, the MAPE of the medium-term forecast is 4.38%, and the MAPE of the long-term forecast is 18.28%. The experimental results show that the proposed model has obvious advantages over the previous model.

Geomechanical investigation of casing collapse using finite element modeling: The role of cement sheath integrity

Casing collapse has been reported in several oil and gas wells all around the world. Cement sheath failure is one of the primary factors that may result in casing collapse. The growing focus on maintaining well integrity over the long term has prompted the creation of more detailed, realistic, and accurate models. Mechanical modeling of the casing-cement-formation setting can reveal the cement's capacity to withstand in-situ stresses, which is critical to sustaining the zonal isolation of the well throughout its lifetime. To date, the literature lacks a rigorous three-dimensional mechanical model to take into account all the geomechanical factors. This study aims to investigate the role of cement sheath failure in casing collapse by developing such a model. To do so, first, a three-dimensional numerical model was built in Abaqus using input data from a collapsed casing case study. Then, the required input data into the model were determined by following a step-by-step geomechanical procedure. Furthermore, to assess the model's accuracy and quality of the mesh, the numerical model was validated against an analytical model for stress distribution around the wellbore. As a preventive measure against casing collapse in upcoming infill wells, a new cement slurry was formulated, and its mechanical characteristics were measured through triaxial tests. The numerical results of the current wellbore cement and newly designed cement were compared to assess the effect of cement sheath integrity on casing collapse. The results revealed that the casing collapse in the case study can be highly attributed to the cement sheath shear failure and migration of the over-pressured formation fluid to the micro-annuli formed at the cement interfaces with the formation and the casing due to plastic deformation. The procedure outlined in this study can be used to design the wellbore cement according to the geomechanical factors to ensure well integrity.

Identifying the operating features of a device for creating implosion impact on the water bearing formation

The object of the study reported in this paper is the parameters of a device for implosion impact on aquifers during well development. The problem of increasing the productivity of aquifers was solved by removing colmatation products formed during the drilling process and restoring the natural permeability of the formations. This could ensure high production of wells and their long-term trouble-free operation. One of the most effective ways to develop wells is implosion impact. However, its use is hampered by the complexity of the structure of existing devices, the high cost of use, and the insufficient reliability of their operation. To overcome this, an original device for implosion impact on aquifers was designed and its operating parameters were determined. A procedure has been devised for determining the maximum permissible sizes of intervals not filled with liquid under the conditions of preventing casing string collapse. The effect of these intervals on reducing the total weight of the casing string was investigated. An optimal well structure was proposed for the conditions of the Tonirekshin field. The critical dimensions of empty intervals were calculated for all wall thicknesses of casing pipes included in the well design. It has been established that the amount of weight reduction of the casing string in the well due to the Archimedean force for field conditions is 43–47 %. Archimedean force increases with increasing pipe wall thickness. Reducing the weight of the casing string reduces the required winch power, allowing the use of lighter drilling rigs. The procedure for preparing for repeated implosion impacts has been studied. The studies performed and the recommendations presented will be effective when drilling and developing wells under the conditions of the Mangistau Peninsula, at the Tonirekshin field.

Prediction of Collapsing Strength of High-Strength Collapse-Resistant Casing Based on Machine Learning

With the increasing complexity of shale gas extraction conditions, a large number of high-strength collapse-resistant casing is applied to the extraction of unconventional oil and gas resources. There are errors in the traditional API collapse strength formula. A high-precision and low-computational-cost model is needed for predicting the strength of high-collapsible casing. The key influencing factors of casing anti-collapse strength were determined as outer diameter, wall thickness, yield strength, ovality, wall thickness unevenness, and residual stress by analyzing the casing collapse mechanism. In response to the key factors mentioned above, a dataset was formed by measuring the geometric parameters of the full-size casing and collecting data on the results of the anti-collapse strength experiment, which was divided into a training set (70%) and a testing set (30%). Three machine-learning algorithms, a neural network, random forest, and support vector machine, were trained to predict the anti-extrusion strength. The correlation coefficient R2, root mean square error RMSE, and average relative MRE were used to evaluate the indexes for model preference evaluation. The results show that machine-learning algorithms have unique advantages in casing anti-collapsing strength prediction. Within which, the neural network prediction model has the best prediction effect, and its characteristics of high precision, low cost and high efficiency are more suitable for the prediction of casing extrusion strength. Its testing set R2 is 0.9733, RMSE is 0.0267 and MRE is 0.0782, and the prediction accuracy can reach 92.2% which is much higher than the API calculation result (63.3%). The network prediction model is suitable for casing anti-collapsing strength prediction and meets the actual prediction requirements.

Optimal defense strategy selection method for CPS considering integrated cyber–physical losses

Cyber-attacks against the cyber–physical power system (CPPS) may lead to major power outages and even system collapse in severe cases. In order to quantify the attack losses and select optimal strategies to defend against cyber-attacks, this paper proposes a computational model of integrated cyber–physical losses based on the theory of interdependent network. Based on the multiple coupling relationship between cyber system and physical network, the monitoring system is regarded as the cyber–physical interaction layer, and the information network operation constraint, physical system load reduction constraint, and monitoring equipment operation constraint are established respectively to analyze the impact on another network after a failed node appears in one layer of network, and proposed the cyber–physical integrated loss objective function. The offensive and defensive processes are abstracted into a two-player zero-sum game model, which evolves into a multi-stage game according to the changes in the system state during the game, and the integrated cyber–physical loss is used as the game gain of both the attacker and defender, and the Minimax-Q algorithm is introduced to solve for the optimal gain and select the optimal defense strategy. Finally, the IEEE 30 node cyber–physical system is used as a simulation example to verify whether the proposed loss calculation model can effectively quantify the losses caused by the attack on the information network and the power grid, and has practical guidance for the selection of the optimal defense strategy.

Evaluation of reservoir subsidence due to hydrocarbon production based on seismic data

Environmental problems associated with depleted oil and gas reservoirs upon long-term production from them are likely to become important challenges in future decades. With the increasing trend of production from hydrocarbon reservoirs, more and more reservoirs across the world are reaching the second half of their life—a fact that places an emphasis on the necessity of investigating what is known as reservoir subsidence. Different analytical and numerical approaches have been introduced for analyzing the subsidence on the basis of the elasticity theory but in the form of case studies, leaving a comprehensive model yet to be proposed. In this work, a formulation was introduced for estimating reservoir subsidence by integrating the rock physics, rock mechanics, and thermo-poroelasticity theories. Then, a modified version of this formulation was developed to calculate compaction in an actively producing reservoir that is suspect of subsidence, as a case study. For this purpose, triaxial hydrostatic tests were carried out on core plugs obtained from the considered reservoir, and then, compaction parameters (i.e., compression index and coefficient of deformation) were obtained at a laboratory scale. In order to evaluate the subsidence at a reservoir scale, the laboratory-scale results and in situ reservoir properties were integrated with well-logging and 3D seismic data at well location to come up with 3D cubes of compaction information. Continuing with the research, time-dependent inelastic deformation was modeled considering continued production for different future periods. The field observations showed that the estimated compaction is not visible at the surface in the form of subsidence due to the high depth and stiffness of the studied reservoir. However, collapse of casing at some of wells drilled into the studied reservoir could be attributed to the reservoir subsidence. Finally, variations of compaction with pore pressure were investigated to propose a model for predicting the subsidence in future periods. Findings of this research can be used to forecast subsidence at well location to take the required measures for avoiding possible casing collapse and/or relevant environmental issues.

Study of compressible turbulent plane Couette flows via direct numerical simulation

Compressible turbulent plane Couette flows are studied via direct numerical simulation for wall Reynolds numbers up to $Re_w=10\ 000$ and wall Mach numbers up to $M_w=5$ . Various turbulence statistics are compared with their incompressible counterparts at comparable semilocal Reynolds numbers $Re^*_{\tau,c}$ . The skin friction coefficient $C_f$ , which decreases with $Re_w$ , only weakly depends on $M_w$ . On the other hand, the thermodynamic properties (mean temperature, density and others) strongly vary with $M_w$ . Under proper scaling transformations, the mean velocity profiles for the compressible and incompressible cases collapse well and show a logarithmic region with the Kárman constant $\kappa =0.41$ . Compared with wall units, the semilocal units yield a better collapse for the profiles of the Reynolds stresses. While the wall-normal and spanwise Reynolds stress components slightly decrease in the near-wall region, the inner peak of the streamwise component notably increases with increasing $M_w$ – indicating that flow becomes more anisotropic when compressible. In addition, the near-wall turbulence production decreases as $M_w$ increases – due to rapid wall-normal changes of viscosity caused by viscous heating. The streamwise and spanwise energy spectra show that the length scale of near-wall coherent structures does not vary with $M_w$ in semilocal units. Consistent with those in incompressible flows, the superstructures (the large-scale streamwise rollers) with a typical spanwise scale of $\lambda _z/h\approx 1.5{\rm \pi}$ become stronger with increasing $Re_w$ . For the highest $Re_w$ studied, they contribute about $40\,\%$ of the Reynolds shear stress at the channel centre. Interestingly, flow visualization and correlation analysis show that the streamwise coherence of these structures degrades with increasing $M_w$ . In addition, at comparable $Re^*_{\tau,c}$ , the amplitude modulation of these structures on the near-wall small scales is quite similar between incompressible and compressible cases – but much stronger than that in plane Poiseuille flows.

Screened Coulomb interaction in insulators with strong disorder.

We study the effect of disorder on the excitons in a semiconductor with screened Coulomb interaction. Examples are polymeric semiconductors and/or van der Waals structures. In the screened hydrogenic problem, we consider the disorder phenomenologically using the so-called fractional Scrödinger equation. Our main finding is that joint action of screening and disorder either destroys the exciton (strong screening) or enhances the bounding of electron and hole in an exciton, leading to its collapse in the extreme case. Latter effects may also be related to the quantum manifestations of chaotic exciton behavior in the above semiconductor structures. Hence, they should be considered in device applications, where the interplay between dielectric screening and disorder is important. Our theoretical results permit one to predict the various excitonic properties in semiconductor samples with different degrees of disorder and Coulomb interaction screenings.

Prediction of Casing Collapse Resistance by 3D Finite Element Modeling

Summary 3D outside diameter (OD) and wall thickness mapping of a casing joint consists of synchronized OD laser scanning and ultrasonic testing (UT) wall thickness measurement at a resolution of every 1 in. along the length and every 1° or 2° around the circumference. This full-length mapping data can then be used to construct a 3D finite element analysis (FEA) model that captures the geometric attributes, including OD, wall thickness, OD ovality, and wall eccentricity, of a casing joint. Together with the actual nonlinear material plasticity model and the measured as-manufactured residual stress, the 3D FEA model can predict the casing collapse strength with good accuracy. Also, the Klever-Tamano ultimate limit-state (KT ULS) collapse equation per API TR 5C3 (2018) together with a moving-average (MA) scheme can calculate the joint’s collapse strength. Results predicted by 3D FEA and KT ULS collapse models are compared to the actual full-scale collapse test results. A 3D FEA model generally produces more accurate results than the KT collapse equation. In addition, both 3D FEA and KT collapse models predict a collapse pressure slightly lower than the actual collapse pressure, which is therefore on the conservative side. The prediction of casing collapse strength can be beneficial to the end user in sorting and ranking the casing joints by collapse resistance, and therefore provides valuable information that can be used in the end user’s risk assessment. Furthermore, the end user may potentially select the joints with the highest predicted collapse strength for the portion of the casing string where the highest collapse resistance is desired. In addition, the OD and wall mapping data together with the actual material tensile properties (yield strength, ultimate tensile strength, and strain hardening parameters) can be used in estimating the internal yield, ductile rupture pressures, and other performance properties. This is outside the scope of this paper and can be pursued in future work. These predicted casing performance properties may then be used in sorting and ranking the joints based on a specific performance property of interest or a combination of performance properties.

Experimental Study on Long-Term Performance of Concrete T-Beam

In recent years, long-span concrete bridges that have been built frequently expose the problems of excessive deflection and concrete cracking, which even lead to bridge collapse in serious cases. The reason is that, in addition to the insufficient estimation of creep and long-term deflection in current regulations, the rapid growth of traffic volume and the tight use of early-age concrete in construction schedules also have a great impact on long-term deflection. However, at present, the calculation methods of long-term performance are mostly based on the results of material performance tests. However, there are relatively few studies that take bridge components as research objects and consider the influence of load and age factors. The long-term performance of concrete beams is examined and the calculation methods of long-term performance are given by considering various loading levels and ages. Specimens are fabricated using a 1:4 scale model of a standard T-beam with a length of 20 m to conduct the experiment. Based on the long-term observation of the test beam, the variation laws of the mid-span deflection of the concrete T-beam and the concrete strain in the compression zone with time are obtained under the aforementioned conditions. Following a comparative analysis of experimental results with computational results based on existing studies and relevant national and international codes, this study proposes and discusses a set of formulas for the assessment of shrinkage and creep. The obtained creep coefficient test results fall between the values of the Chinese specification and those of AASHTO, where ASSTO is the lower limit and the Chinese specification is the upper limit. The long-term deflection is as follows: 40% of the one-year value at one month, 66% of the one-year value at three months, and 80% of the one-year value at six months. However, the long-term deflection coefficient of beams with an early loading age is larger than the current standard, and the deflection coefficient of T-beams with three-day loading age reaches 6.0. We compare and discuss the test results with the calculation results and related codes obtained in different studies conducted at home and abroad. Based on our present findings, we propose formulas for shrinkage and creep evaluations.

A case of chronic schistosomiasis in a Dongola stallion (Equus ferus caballus Linnaeus, 1758) from Nigeria.

Schistosomiasis is a worldwide snail-borne parasitic infestation of man and animals with acute or chronic phases having devastating sequelae. The present case report focused on post-mortem examination of a cachexic Dongola stallion (Equus ferus caballus Linnaeus, 1758) in Abuja, Nigeria, that failed to respond to treatment. Typical dense collagenous granulomatous lesions with marked inflammatory responses and fibrosis occurred in the liver and several visceral organs of the horse along with other lesions indicative of systemic collapse. Special Ziehl-Neelsen and Periodic Acid-Schiff staining as well as microbial culture returned negative results to rule out acid-fast bacilli, fungal, and other bacterial involvement. In addition, the presence of a yellowish-brown eggshell within fibrosing granulomatous lesions led to the diagnosis of chronic schistosomiasis. Prolonged malnutrition under harsh and changing increment weather conditions with lack of medical care following the infection might have predisposed the horse to the recorded systemic collapse in the present case. The dearth of information on the ante-mortem evaluation of acute equine schistosomiasis cases notwithstanding, the observed lesions/cellular changes reinforced associated multi-organ damages and systemic collapse in chronic cases. Our findings highlighted the pathological presentations and prognosis of chronic schistosomiasis and its triggers, especially in endemic areas, and in horses that often do not present obvious clinical manifestations.

Hydrologic restoration of anthropoentically altered springs in the Sheldon National Wildlife Refuge in the Great Basin, USA

Springbox capped springs divert water for livestock and threaten spring conservation in the Great Basin. Springbox restoration is used to increase water availability at riparian zones and wet meadows. The purpose of our study was to compare six restoration methods used to increase soil moisture. We used a BACI design to compare percent soil moisture before and after restoration at 24 spring sites in Northwestern Nevada, U.S.A. Percent soil moisture was measured at 5-, 15-, 30-, and 45-cm depths during spring and summer months. Year 2017 was wetter than 2016 causing an increase in percent soil moisture in all restoration treatments. Empty springbox cases, cases filled with sand, and caseless gravel-filled springs produced the greatest increase in percent soil moisture at all depths. We recommend sand-filled casings because these funnel water to the surface while sand prevents casing collapse. We recommend sand over gravel because sand is easier to displace as water flows to the surface. The ratio of δ18O/d16O suggests that springs are fed by shallow groundwater derived from recent precipitation. Inter-annual reductions in precipitation driven by climate change may be the ultimate force determining the preservation of Great Basin spring ecosystems.

Detection and Location of Steel Structure Trestle Surface Cracks Based on Consumer-grade Camera System

Because the steel structure trestle has been in service under heavy load for a long time, the steel structure trestle is prone to cracks around the welds or bolt holes, which can lead to structural collapse in severe cases. Aiming at the characteristics of stable and high-quality images obtained by the unmanned consumer-grade camera monitoring system, this paper proposed structure health monitoring (SHM) system which is based on consumer-grade camera. The SHM system can identify crack damage and locate steadily in long term, which provides the technical support of practical application in intelligent SHM system. The method first performed edge detection on the trestle structure, followed by pixel-level semantic segmentation and crack localization. Canny edge detection algorithm was used to identify trestle structures in the camera image. The panorama trestle structure was divided into areas of suitable size, and the camera focused on each divided area one by one. Then the improved DeepLab V3+ model was trained by constructing global and local datasets. Then the improved DeepLab V3+ model was used to perform pixel-level semantic segmentation on the trestle images of the divided regions. Finally, based on the Speeded Up Robust Features and combined with the image, a panorama crack location output method was proposed. The system was used to test a section of a trestle in a coal mining industrial park, and the system showed that the method could efficiently and accurately identify and locate the crack damage.

Study on the whole process application of advanced grouting pipe shed support under urban complex stratum conditions

The stability control of surrounding rock is always one of the important problems in tunnel construction. As a representative of tunnel pre-construction technology, advance grouting pipe roof support method is widely used in underground space engineering under various complex geological conditions, especially in strata with many fractured rock masses and rich groundwater content. Due to the complexity of the application of advance grouting pipe roof method, few studies have been conducted on the whole process of pipe roof application in actual projects. Taking the shield departure project of Guangzhou Metro Line 13 as the background, this paper uses the modified BQ method to grade the surrounding rock environment of the tunnel from the perspective of the stability evaluation of the surrounding rock of the tunnel. The result shows that the revised surrounding rock is grade v. further combining with the geological exploration report, it is found that the rock mass joints and fissures are large and may further develop under the change of the surrounding rock mass stress environment, and the formation water content is large. The surrounding rock is prone to large deformation under the action of groundwater, and even lead to surface collapse in serious cases. Therefore, it is necessary to adopt the advance grouting pipe roof support method. Subsequently, the influence of different pipe roof design parameters such as pipe roof diameter, number of pipe roofs, reinforcement thickness and layout range on its support effect is analyzed by using finite element software, and appropriate parameter values are determined and applied to the background project. Finally, considering the measurement error existing in actual monitoring, a dynamic safety evaluation method of tunnel structure based on reliability theory is proposed, and the background project is analyzed and evaluated by this method. The analysis shows that the tunnel structure with advance grouting pipe roof support meets the safety requirements, confirms the effectiveness of the design parameters, and can provide reference for tunnel construction under the same geological conditions.

INVESTIGATING THE IMPACT OF ACHI (BRACHYSTEGIA EURYCOMA) ON THE THICKENING TIME OF CEMENT

In recent times, more wells are being drilled and producing in the petroleum industry. To prevent early workover resulting from casing collapse caused by corrosion, shattering of cement sheath during perforation and fracturing, and to protect the integrity of the well, it is important to use properly designed cement slurry with appropriate additives to protect the well from the formation. The development of adequate thickening time cement is a critical task in cementing operations today. Achieving suitable thickening time of oil well cement ensures both prevention of lost circulation and a long wait on cement time. With this in mind, this research work shows a comparative study of the thickening time of oil well cement with achi and without achi contamination under different temperature of 130 ℉, 150 ℉, 200 ℉, and 250℉ and pressure conditions of 1000 psi, 1500 psi, 2000 psi and 3000psi respectively for all the experiment conducted. The thickening time of cement slurry without achi content at 70 Bc were 205, 215, 202 and 200 minutes respectively. The experiment was also conducted under different achi content ranging from 2 g, 4 g, 8 g, 10 g to 12g. The results and analysis were compared. The result with 2g achi content were 164, 147, 146, and 141 minutes. The results with 4g achi content were 127, 131, 130, and 124 minutes. The results with 8g achi content were 71, 69, 75, and 65 minutes, while the results at 10g achi content were 67, 62, 63, and 60 minutes. The results with 12g achi content were 63, 62, 60, and 56 minutes under the temperature and pressure respectively. The data obtained from the experiment signifies that introducing achi and altering the temperature and pressure to the cement slurry has a significant effect on the properties of the cement by accelerating the thickening time.

Loose bolt detection method based on wavelet packet decomposition with CNN

Loose bolts in PV mounts can affect the smooth operation of the system. If the loose bolts are not detected in time, the PV modules may fall off and cause the mounts to collapse in serious cases. The ultrasonic wavelet packet decomposition (WPD) combined with convolutional neural network (CNN) is proposed as a detection method to address the problem that the ultrasonic signal collected when the bolt is loose indistinctively. First, the ultrasonic signal with bolt loosening information is decomposed into four layers of wavelet packets to extract the energy composition of the feature vectors of each sub-band signal; second, the CNN model is designed and the network is trained with the feature vectors as samples; finally, the discrimination of bolt loosening conditions is achieved. The feasibility of the method is verified through experiments, and the experimental results show that the accuracy of the model is improved from 95.64% to 99.92% compared with the original data training model, and from 86.96% to 99.92% compared with the support vector machine (SVM).