Cement Quality Research Articles

Diagenetic imprints in the reservoirs of Agbada Formation, Niger Delta Basin: Implication for reservoir quality and appraisal of calcite cement

The main exploration targets for hydrocarbons in the Niger Delta Basin are within the Agbada sandstone reservoirs. The current study utilizes a multitechnical approach (SEM-MLA, SEM-EDS, XRD and LA-ICP-MS) to evaluate the roles of framework composition and diagenetic processes, particularly calcite cementation on reservoir quality in Miocene intervals of the Agbada Formation sandstone, Niger Delta Basin. Petrographic analysis reveals that the sandstones are feldspatho-quartzose to quartzose sandstones, with a preponderance of quartzose sandstones. The overall diagenetic imprints suggest minimal compaction and lack of pervasive cement, which have contributed significantly to the high porosity. Although the degree of mechanical compaction is generally low, it has comparatively exercised a better control on porosity than the growth of cement, excluding some intervals with considerable cementation (siderite and ferroan calcite) where compactional porosity-loss was minimal. The occurrence of ferroan calcite cement (CaCO3 = 95.9 ± 0.4, MgCO3 = 0.8 ± 0.1, FeCO3 = 2.9 ± 0.2 mol%) is generally small, probably discontinuous and unlikely to represent significant barriers to fluid flow with their localized influence, but understanding their locally significant influence may still contribute to building good reservoir models. Petrographic observations suggest that the precipitation of “poikilitic” calcite was early, but the shale normalized REY patterns do not mimic seawater patterns (Y/Ho ratios; 36.3 ± 1.6) due to possible contributions from clastic or detrital grains and/or incorporation of particulate matter that can preferentially scavenge LREEs from the overlying water column. A possible concern during reservoir production is the occurrence of clay mineral matrix (mostly kaolinitic) anticipated to cause the production of fines and formation damage, but this can be mitigated with proper reservoir management.

Planning of Marketing Strategy based on the Results of Analysis of Profitability Ratios and Activity Ratios (Case Study: PT Semen Indonesia Tbk)


 Semen Indonesia (Persero) Tbk is a manufacturing company engaged in cement production. This product is widely used for infrastructure development, so good cement quality is expected. Producers are expected to produce cement in accordance with consumer expectations and needs. The aim is to obtain high sales turnover. To meet sales targets, a good strategy is needed that is based on real conditions in the field. One of them is financial performance. Based on the financial performance report, especially the profit and activity ratios, it will be analyzed and used as a reference in determining sales strategies. The results of the financial performance analysis and SWOT analysis can formulate a sales strategy design.

Monitoring and elimination of intercasing pressure

Background: The appearance of intercasing pressure in many cases is associated with inadequate quality of primary cementing. Despite the fact that many studies are aimed at preventing problems of primary cementing, at improving the quality of well completion, it should be noted that the problem of intercasing pressure at existing gas and gas condensate wells is increasing.
 Aim: The purpose of this work is to study and eliminate wells with intercasing pressure at the Amangeldy gas condensate field.
 Materials and methods: This paper presents the procedure for preparing the well and carrying out the elimination of intercasing pressure, as well as the chemical components of cementing slurry.
 Results: The conducted studies and measures on wells No.121; No.105; No.103 and No.101 showed a positive result and the effectiveness of the composition of cementing slurry.
 Conclusion: The presented technology for the elimination of intercasing pressure and the composition of the cementing slurry can be widely used in many fields of Kazakhstan.

The method of improving the cementing quality of the interface in deep coalbed gas well through the wetting reversal technique

ABSTRACT Coalbed methane, also known as coalbed methane gas, is a natural gas formed by the biogeochemical and pyrolysis processes during the formation and evolution of coal and stored in coal seams. Compared with conventional coalbed methane, deep coalbed methane has a rich resource and is an important substitute for natural gas increase, storage, and production. During the process of coalbed methane extraction, the inability of coal rock to bond well with cement slurry leads to a decrease in the quality of cementing, which has become one of the main problems affecting the extraction of deep coalbed methane. To address this issue, this paper first analyzes the microstructure of the coal rock-cement interface to reveal the mechanism of strengthening the coal rock-cement interface bonding. Then, using the wettability of coal rock as an evaluation index and the surfactant wetting modification method, the paper modified the surface of coal rock to enhance its hydrophilicity, optimized the suitable coal rock wetting modification agent, and finally evaluated the enhancement effect of the coal rock wetting modification agent on the quality of the coal rock-cement interface bonding through interface bonding experiments. The research results indicate that the hydrophobicity of coal rock surface is the main reason for the poor bonding between coal rock and cement. The three primary surfactants can improve the water wettability of coal and rock surfaces by 41.57%–52.95%, among which AES surfactant has the best improvement effect. After soaking in 0.5% AES solution at 85°C for 8 min, the hydrophilicity of coal rock can be increased by 72.3%. There are no obvious cracks between the coal rock-cement interface, and the bonding quality of the coal rock-cement interface has increased 2.69 times. Coal rock surface wetting modification can effectively enhance the interface bonding effect, which is conducive to improving the quality of cementing of deep coalbed methane.

Evaluation of the casing strength reliability in deep gas well by taking into account the cement quality and strength uncertainty: Method, analysis and application

Casing damage is one of the most challenging engineering issues in deep gas wells, leading to significant economic losses and severe incidents such as gas leaks or high annular pressure. According to field data analysis, in addition to traditional factors like stress, temperature, or corrosion, cement sheath quality also impacts casing damage. Hence, this paper establishes a three-dimensional finite element model for casing-cement sheath -formation considering cement sheath quality. It discusses the impact of different cement sheath defects (such as void and eccentricity) on casing stress distribution under the influence of in-situ stresses, high-pressure fluids, and annular pressure. The analysis reveals that under adverse conditions, poor cement sheath quality exacerbates stress on the casing, increasing the risk of casing failure, with the degree of impact being cement void angle > cement eccentricity > cement void thickness. Based on this, a nonlinear fitting of changes in casing equivalent stress is conducted to establish a model for calculating casing external loads under cement void or eccentricity conditions. Considering the dual uncertainty of casing external load and strength parameters, a casing reliability evaluation method is established based on the external load calculation model and stress-strength interference theory. The reliability of casing strength is assessed and analyzed using a practical well in an oil field as an example. The results indicate that compared to traditional safety factor methods, the reliability evaluation method established in this paper can more intuitively and accurately display variations in casing reliability, offering a scientific basis for optimized design solutions. Optimizing cement sheath performance (such as reduced cement elastic modulus and Poisson's ratio) and enhancing cementing quality (by preventing cement voids and eccentricity) effectively reduce the risk of casing failure.

Alabama Field Project to Evaluate Variability in Soil–Cement Specimens Compacted with the Plastic Mold Device

The plastic mold compaction device (PM Device) was developed in Mississippi to compact cementitiously stabilized soil inside plastic molds to improve soil–cement quality by adding value during design and construction activities. The PM Device has been incorporated as an AASHTO provisional standard (AASHTO PP92-19) and, to date, prevailing activities have been Mississippi Department of Transportation projects and have included controlled laboratory evaluations and field projects. This paper goes beyond previous efforts, to document a field study in which the PM Device was successfully used on an Alabama Department of Transportation project to evaluate its effectiveness within another state’s construction specifications. The PM Device was capable of capturing quantifiable variation in mechanical properties over the duration of the construction project, as well as producing similar mechanical properties to cores taken from the compacted pavement surface. Additionally, molds described in AASHTO PP92-19 were compared with one another to evaluate their potential within the standard practice. AASHTO PP92-19 protocols were sufficient to produce viable, repeatable test specimens within another state department of transportation construction environment for quality control and quality assurance.

Mineral, Chemical and Technical Characterization of Altered Pyroxenic Andesites from Southeastern Spain for Use as Eco-Efficient Natural Materials

Climate change is already an undeniable reality, and it is a direct consequence of our society’s lifestyle and the indiscriminate use of certain materials, such as Portland cement, which causes the emission of gases and waste that contributes to the greenhouse effect. The object of this work is to present the results obtained from research on pyroxenic andesites that have become altered to zeolite and their use as alternative, eco-efficient materials that improve the quality of cement through a standardized partial substitution. In this work, four samples of pyroxenic andesites altered to zeolites (PAAZ) and two samples of unaltered andesites (UPA) were analyzed. The methods used in this study are as follows: petrography of thin section (PTS), chemical analysis of X-ray fluorescence (XRF) and phase determination by X-ray diffraction (XRD). Other tests were carried out to determine the quality of the PAAZ from a technical and practical application point of view, such as chemical analysis of pozzolanicity (CPT) at 8 and 15 days, as well as mechanical compression tests at 2, 7, 28 and 90 days. Petrographic and phase analyses show that the original mineral components of the samples such as pyroxene, amphibole, plagioclase and mica were leached and replaced by more than 90% with mordenite and smectite. XRF analyses indicates an anomalous rise in SiO2, a drastic reduction in alumina Al2O3 and a significant increase in alkaline compounds over alkaline-earth compounds in samples of altered pyroxenic andesites (PAAZ) with respect to samples of unaltered andesites (UPA). The pozzolanicity test establishes that the samples of unaltered andesites do not behave like pozzolans at 8 or 15 days; however, altered andesites experienced remarkable pozzolanic reactivity in the same periods. The mechanical compression tests carried out on specimens made with PAAZ and Portland cement showed a growing increase in mechanical resistance from 2 days (15.2 MPa) to 90 days (72.1 MPa). These results suggest that pyroxenic andesites altered to zeolite can be an ideal alternative to partially replace Portland cement, which in turn could contribute to the preservation of the environment and a more rational use of traditional resources.

Measurement of wellbore leakage in high‐pressure gas well based on the multiple physical signals and history data: Method, technology, and application

AbstractLeakage is one of the most serious challenges for the safe production of high‐pressure gas wells for its high risks, including abnormal annular pressure, natural gas accumulation, and environment pollution, but available methods can hardly accurately measure the leakage type and depth, which are the key parameters for the rigless leakage repair and risk assessment. Therefore, this paper proposes a method to measure the leakage based on the characteristics, which combines qualitative and quantitative measurement together. Qualitative measurement considers the annular pressure, tubing pressure, liquid level, cement quality, and workover history. Quantitative measurement is determined by noise logging, electromagnetic logging, pressure logging, and temperature logging. The logging should be optimized according to the qualitative measurement. The method was successfully applied in high‐pressure gas well belonging to Tarim Oilfield. Two potential leakage types are provided based on the annular pressure, liquid level, cement quality, and workover history, including tubing leakage and linger hanger leakage. Based on the potential leakage types, the pressure difference, logging devices string, stopping length, and time are optimized to make the engineering logging reliable. Through measurement, two leakage points are found in tubing string. One is tubing body crack at the depth of 2724 m and the other is tubing thread leakage at the depth of 5211.7 m, which well matches the production data.

Cementing Quality Prediction in the Shunbei Block Based on Genetic Algorithm and Support Vector Regression

There are a number of factors that can affect the quality of cementing, and they constrain each other. Current cementing quality prediction methods are still in the stage of development, and it is difficult to establish an analytical model for cementing quality prediction that meets the strict requirements of cementing design. In order to accurately predict the cementing quality in the Shunbei block of the Northwest Oilfield, in this study, we established a cementing quality prediction model based on support vector regression (SVR) and optimized the penalty parameter and kernel parameter by using grid search (GS), a Bayesian optimization algorithm (BOA), and a genetic algorithm (GA), which improve the prediction accuracy of SVR. The results show that the smallest root-mean-square error and average relative error (2.318% and 7.30%, respectively) and the highest accuracy are achieved when using GA–SVR as compared to SVR, GS–SVR, and BOA–SVR. Therefore, GA–SVR is suitable for cementing quality prediction in the Shunbei block.

Manufacture of potassium chloride from cement kiln bypass dust: An industrial implementation case for transforming waste into valuable resources

The recirculation of chlorine within the kiln presents a major hurdle in co-processing domestic waste in cement kilns. This chlorine enrichment not only adversely affects the quality of cement, but also pose a serious challenge to the subsequent eco-friendly disposal of kiln dust. To solve this problem, a proper bypass system has been implemented in this study on a 4000 t/d new dry process cement rotary kiln, and the collection of chlorine-rich bypass dust outside the kiln (30 t/d) has been achieved. In addition, a comprehensive and innovative system has been developed, including water washing and subsequent triple-effect salt extraction, to achieve leaching of K+ and Cl from the bypass dust in the water rinsing liquid, while effectively removing harmful metal ions such as Pb2+. Finally, the extraction of high-purity KCl salt (6 tons/day, purity of 90 %) has been successfully achieved. It is worth noting that high-temperature flue gas rich in CO2 has been used to precipitate certain heavy metal ions, while steam from the waste-heat power generation system has been employed as a heat source for the potassium salt evaporation process. More importantly, all the materials, except for the KCl salt product, are returned to the cement kiln system without causing any secondary pollution. This study not only effectively addresses the negative impacts of chlorine element circulation within cement kilns during domestic waste co-processing, but also achieves a highly innovative engineering practice of transforming waste into valuable resources from kiln dust to high-purity KCl products. In brief, this work provides a reference example for future approaches to clean production, carbon reduction and resource utilization in the cement industry.

Graphene Oxide in Construction: A Comprehensive Review on the Prospects, Challenges, and Sustainable Cement Reinforcement

The growing demand for cement production to support the rapid growth of the construction industry has resulted in a significant contribution to global carbon emissions due to the high energy requirements of cement production. Addressing this issue requires the development of eco-friendly cement modifiers/additives. Graphene, known for its exceptional properties, has emerged as a versatile material in various domains, including construction. Its incorporation into cement has exhibited promising prospects, surpassing geopolymer performance and enhancing cement quality. Nevertheless, challenges persist, such as inadequate dispersion in concrete mixtures and quality control issues during large-scale production. Harnessing the potential of graphene oxide can revolutionize cement performance and contribute to a more sustainable construction industry. Addressing dispersion challenges and ensuring successful large-scale production are pivotal steps towards realizing these benefits. This comprehensive review investigates the potential of graphene oxide in the construction sector, specifically focusing on its capacity to reinforce cementitious composites and highlighting the associated implementation challenges, paving the way for more sustainable cement production with a touch of scientific excellence.

Detection of Melanocortin Receptor Type 4 (MC4R) Gene in Semen of Etawah Crossbreed and Senduro Goats

Etawah crossbreed and Senduro goats as superior local goats and biological genetic resources that must be preserved in Indonesia. Melanocortin receptor type 4 (MC4R) is the primary gene that regulates food intake and energy balance which can be used as a candidate marker for livestock selection genes. This study aimed to analyze the comparison of cement quality and detect the profile of the MC4R gene in Etawah crossbreed and Senduro goat semen. The samples of this study were Etawah crossbreed and Senduro goat semen. Macroscopic examination of cement includes the evaluation of volume, consistency, odor, color, and pH. Microscopic examination of semen includes motility, abnormalities, and spermatozoa concentration. Examination of motility was performed in the condition of fresh semen, after the addition of diluents, and post-thawing of frozen straw. The polymerase chain reaction (PCR) method was performed to amplify specific fragments of the MC4R gene. There was a decrease in spermatozoa motility before freezing and post-thawing frozen semen compared to fresh semen. The quality of frozen straw post-thawing Etawah crossbreed and Senduro goat was still worth using for artificial insemination and in vitro embryo production. The MC4R gene can be detected in liquid and frozen semen from Etawah crossbreed and Senduro goats using a PCR test in the form of a single band along 642 bp.

ÉTUDE DE L’IMPACT DE L’UTILISATION DE L’AGENT DE MOUTURE MAGA C212 SUR LE PROCESSUS DE BROYAGE ET LA QUALITÉ DU CIMENT A LA SCB – CIMENT BOUCLIER

The theme worked entitled “Study of the impact of the use of the MAGA C212 grinding agent on the grinding process and the quality of cement at SCB-Cement BOUCLIER”. The methodology adopted consisted of conducting the tests on the mini-mill and extrapolating the results obtained to the main mill. The tests are summarized in the determination of the load of the mini-crusher with regard to the wear of the balls, the optimum flow rates of the mini-crusher without and with grinding agent using a test sample of cement or white sample, the optimum dosage of grinding agent for an optimum flow rate, the production of cement under the optimum conditions identified and the physico-chemical characterization of the cement produced, namely the loss on ignition and the percentage of SO3, the Specific Blaine Surface Area, the percentage of Refusal on 80 µm and 160 sieve µm, and the compressive strengths at 2, 7 and 28 days. Thus, thanks to the use of MAGA C212 as a grinding agent under production conditions of 350 g/T and a constant flow rate of 15 kg/h, a significant improvement is induced compared to the control, on the fineness of 21, 12%, a reduction in refusal at 80 µm of 3.5% and a gain in resistance at 28 days of 13%. The optimal production conditions identified with the MAGA C212 grinding agent are 245 g of MAGA C212 per ton of material to be ground for 18 kg/h flow rate. At this dosage we obtain a gain of 20% in flow rate, an improvement in resistance at 28 days of 4.39% and an energy gain of 16.7%. Extrapolation of our experimental results to the real conditions of the main grinder allowed us to estimate an increase of 10% in yield, a reduction of 15% in the rate of MAGA C212 grinding agent, and a reduction of 8.35 % of the energy consumption of the main crusher.

Determination of cement quality via optical spectroscopy and machine learning-based image recognition

Recent events in Colombia like the collapse of the Space building in Medellin, or the Chirajara motorway bridge have undermined public opinion generating a bad perception regarding the construction industry. Some of these problems were related to structural design flaws but also poor quality materials. To partially tackle this problem a novel instrument was designed to assess the quality of the cement by capturing inelastic scattering vibrational modes of the C2S, C3S, and CSH. By combining the spectral information with a machine learning model able to recognize the intensity levels of the spectral bands associated with a high quality cement it was possible to detect low quality samples. After the training process of the neural network, the tool successfully recognized 95% of the samples provided.

Investigation on the synergy enhancement effect and mechanism of consolidation/thermal conductivity of CNTs-composite cement

Geothermal well is completed generally with a cemented casing across the heat source, while the existing casing cement generally suffered from insufficient performance to meet the demand of actual medium-deep geothermal well construction. In view of this, combining theoretical analysis and experimental research, a new type of carbon nanotubes (CNTs) composite cement for geothermal exploitation was successfully developed by introducing thermal conductivity fillers, heat stabilizing material, nanomaterial and additives to synergistically regulate the comprehensive performance of casing cement. The evaluation of the high-temperature rheology and stability of slurry, and the compressive strength and thermal conductivity of cement stone was carried out based on the normative means. And the results showed that cement slurry had excellent high-temperature performance. The 28d compressive strength (With the curing condition of 150 °C & 20.7 MPa) of cement stone reached 8.15 MPa and the thermal conductivity was stabilized at 2.236 W/(m·K), both of which were at a high level in similar studies. Finally, a combination of hydration process analysis (TGA and XRD), microstructure study (MIP and SEM) and heat transfer mode study (Energy spectrum scanning) was used to summarize the nano-composite cement consolidation/thermal conductivity mechanism. Analysis showed that CNTs could play the effect of "pore filling" and "bridging" hydration products, and the additives could participate in the hydration reaction and regulate the hydration process. In addition, the heat transfer mode of the cement matrix was in accordance with the theory of heat conduction path. The study results provide a new idea to improve the cementing quality of cement and optimize the heat extraction efficiency of geothermal wells from the perspective of material development.

Prediction of Cement Slurry Density Based on AMIndRNN

Cement slurry density is one of the key factors affecting the consolidation effect of oil casing and wellbore, and its value has a direct impact on the quality of cementing and construction safety. In the traditional cementing operation, the professionals perform experiments based on information from adjacent Wells to obtain fuzzy cement density, and then constantly adjust the final cement density in the actual operation, which costs a lot of labor and time, and is not good for real-time operation. In response to the above problems,This paper proposes AMIndRNN(Attention Mechanism combined with Independently Recurrent Neural Network) for cement slurry density prediction, and optimizes IndRNN by introducing SMU activation function. The comparison experiment between AMIndRNN model and baseline model shows that AMIndRNN model has obvious advantages in various performance indexes, which can be used to guide the design of actual cement slurry density.

Soft sensor modeling of cement clinker quality: a novel timing matching technique and data decoupling approach

Clinker free calcium oxide (f-CaO) content is an important indicator of cement quality. Considering the production characteristics (strong coupling, time-varying delay) in the cement process industry, a soft sensor model was developed by combining various methods. First, a new decoupling method is proposed to deal with the strong coupling between variables, which achieves data decoupling between process variables through the attention mechanism and the long short-term memory network. Second, a novel time-series matching technique is proposed to handle the time-varying delays, which utilizes a window selection mechanism to adaptively select the time period in which each process variable influences the target variable. Third, the critical features of the variables are extracted by a one-dimensional convolution network (1D-CNN). Last, a combination of the data decoupling method, window selection mechanism, and 1D-CNN is applied to develop a soft sensor model (ADM-WGM-CNN), which implements the measurement of f-CaO content. The experimental results demonstrate that the ADM-WGM-CNN model has better measurement performance.

Application of TUSSIM with a variable Tromp curve for predicting optimal operation of multi-compartment mills with various ball size distributions

A true unsteady-state simulator (TUSSIM) for ball milling was integrated with a variable Tromp curve for classification to simulate and optimize closed-circuit, multi-compartment cement ball milling. Using representative model–operational parameters from available literature, we first investigated the system dynamics for a two-compartment mill. Then, various simulations examined the impacts of closed-circuit vs. open-circuit operation, number of compartments, and various ball size distributions. Our results suggest that integrating an air classifier into an open-circuit ball mill can increase the production rate by 15% or increase the cement-specific surface area by 13%. A single-compartment mill entails a pre-milled feed for proper operation, whereas a two-compartment mill yields a finer cement product than a three-compartment mill. Uniform mass distribution of balls led to slightly finer product than uniform surface area or number distributions, while the impact of a classifying liner was negligibly small. Finally, we identified optimal ball mixtures in a two-compartment mill using a combined global optimizer–DAE solver, which suggests 14% capacity increase with desirable cement quality. Overall, TUSSIM’s results are not only in line with limited, full-scale experimental studies and industry best practices, but also provide fundamental process insights, while enabling process optimization with tailored ball mixtures in different compartments.

An evaluation of the effectiveness of implementing technological solutions based on digital technologies to improve well casing quality

The article presents the process of forming measures based on digital technologies to improve the quality of well cementing at the fields of Western Siberia. The problem associated with the low quality of input information due to the use of several independent sources was identified and solved. The economic efficiency of the developed methods for reducing the labour costs of data collection for modelling using machine learning algorithms is demonstrated. If the solutions developed are implemented, there is a prospect of reducing the cost of repair and insulation work. Key information is provided about the hypotheses generated and their objectives. The authors of the article describe the method of using various mathematical algorithms to analyze the results of industrial experimental work. The efficiency of the developed solutions is evaluated by comparing the results of cementing experimental wells and wells built using the basic technology. The dynamics of cement quality growth in the fields of Western Siberia are summarised as a general result. As a result of the experience gained, the solutions have been adapted and are in the process of being re-implemented in order to make a final assessment of their effectiveness.

Less early subsidence of cemented Exeter short stems compared with cemented Exeter standard stems in Dorr type A femurs.

The Exeter short stem was designed for patients with Dorr type A femora and short-term results are promising. The aim of this study was to evaluate the minimum five-year stem migration pattern of Exeter short stems in comparison with Exeter standard stems. In this case-control study, 25 patients (22 female) at mean age of 78 years (70 to 89) received cemented Exeter short stem (case group). Cases were selected based on Dorr type A femora and matched first by Dorr type A and then age to a control cohort of 21 patients (11 female) at mean age of 74 years (70 to 89) who received with cemented Exeter standard stems (control group). Preoperatively, all patients had primary hip osteoarthritis and no osteoporosis as confirmed by dual X-ray absorptiometry scanning. Patients were followed with radiostereometry for evaluation of stem migration (primary endpoint), evaluation of cement quality, and Oxford Hip Score. Measurements were taken preoperatively, and at three, 12, and 24 months and a minimum five-year follow-up. At three months, subsidence of the short stem -0.87 mm (95% confidence interval (CI) -1.07 to -0.67) was lower compared to the standard stem -1.59 mm (95% CI -1.82 to -1.36; p < 0.001). Both stems continued a similar pattern of subsidence until five-year follow-up. At five-year follow-up, the short stem had subsided mean -1.67 mm (95% CI -1.98 to -1.36) compared to mean -2.67 mm (95% CI -3.03 to -2.32) for the standard stem (p < 0.001). Subsidence was not influenced by preoperative bone quality (osteopenia vs normal) or cement mantle thickness. The standard Exeter stem had more early subsidence compared with the short Exeter stem in patients with Dorr type A femora, but thereafter a similar migration pattern of subsidence until minimum five years follow-up. Both the standard and the short Exeter stems subside. The standard stem subsides more compared to the short stem in Dorr type A femurs. Subsidence of the Exeter stems was not affected by cement mantle thickness.