Derivative Curves Research Articles

Screening of the protein C pathway abnormality-related thrombophilia by using thrombomodulin-mediated tissue factor-triggered clot waveform analysis.

Absolute or relative protein (P)C pathway abnormalities (PC deficiency, PS deficiency, antiphospholipid syndrome (APS), factor (F)V-abnormality, and high FVIII level) cause thrombophilia. Although screening assays for these thrombophilias are available, one utilizing clot waveform analysis (CWA) remains unknown. We aimed to establish a CWA-based screening assay to distinguish PC pathway abnormality-related thrombophilia. Samples were reacted with tissue factor (TF)/phospholipids and recombinant thrombomodulin (rTM; optimal 20 nM), followed by CWA measurement. The peak ratio (with/without rTM) of the first derivative curve of clot waveform was calculated. The peak ratio in healthy plasmas (n=35) was 0.36 ± 0.13; hence, the cutoff value was set to 0.49. The peak ratios in plasmas with PC deficiency, PS deficiency, high-FVIII (spiked 300 IU/dl), and APS were higher than the cutoff values (0.79/0.97/0.50/0.93, respectively). PC-deficient plasma or PS-deficient plasma mixed with normal plasma (25%/50%/75%/100% PC or PS level) showed dose-dependent decreases in the peak ratios (PC deficient: 0.85/0.64/0.44/0.28; PS deficient: 0.69/0.53/0.40/0.25), suggesting that the peak ratio at ≤50% of PC or PS level exceeded the cutoff value. The peak ratio in FV deficiency with FV ≤25% was higher than the cutoff value. FV-deficient plasma spiked with 40 IU/dl rFV-R506Q (FVLeiden ) or rFV-W1920R (FVNara ) showed >90% peak ratios. rTM-mediated TF-triggered CWA might be useful for screening PC pathway abnormality-related thrombophilia.

Pressure transient analysis for multi-wing fractured vertical well in coalbed methane reservoir based on fractal geometry and fractional calculus

In this paper, a semi-analytical mathematical model of pressure transient analysis (PTA) for multi-wing fractured vertical well (MWFV) in coalbed methane (CBM) reservoir is proposed, which considers the complexity of porous media by fractal geometry, the anomalous diffusion based on fractional calculus and the stress sensitivity represented by the exponential expression. Then through line source theory, dimensionless transformation, Pedrosa transformation, and other methods, the solution of the bottom hole pressure is obtained. At last, the PTA curve is presented by the Stehfest inversion method, and seven flowing regimes are identified. It can be observed that after introducing fractal geometry and fractional calculus, the PTA curve is quite different from the traditional curve in the slope of the derivative curve. The influences of related parameters are discussed, including mass fractal dimension, anomalous diffusion coefficient, number of hydraulic fractures, fracture angle, and stress sensitivity factor. Relevant results can provide better guidance to understand the CBM production performance in MWFV.

Temperature Transient Analysis of Naturally Fractured Geothermal Reservoirs

Summary A potential approach to develop geothermal energy is by producing low-to-medium temperature fluids from naturally fractured geothermal reservoirs (NFGRs). Pressure transient analysis (PTA) is the most common approach to characterize such reservoirs for improving development efficiency. However, pressure inversion leads to nonuniqueness and cannot be used to estimate thermal properties. Moreover, reliable methods to evaluate the development potential of fractured geothermal reservoirs are lacking. To address the gap, this work aims to study the temperature behavior and explore a suitable analysis method for characterizing geothermal reservoirs and evaluating development potential. We developed numerical and analytical models to analyze the temperature behavior in NFGRs. The developed models account for the Joule-Thomson [J-T effect (μJT)], adiabatic heat expansion/compression effect (ζ), reservoir formation damage, heat conduction, and convection effects. The developed numerical solution is verified and found to agree with the proposed analytical solutions. The results show that temperature transient analysis (TTA) with constant or temperature-dependent μJT and ζ assumption leads to a minor difference when reservoir temperature changes significantly. Moreover, three heat radial flow regimes (HRFR) and a thermal interporosity regime with a V-shape characteristic have been identified. The results also show that temperature data provide information not accessible by PTA. The results reveal that temperature derivative curves signify a “hump” when formation around a wellbore is damaged, and the temperature data can be used to characterize the skin-zone radius and permeability. It is demonstrated that the properties such as J-T coefficient, effective adiabatic heat expansion coefficient, and fracture intrinsic porosity can be estimated using TTA. The results indicate that fracture thermal storativity (ωT) and matrix thermal interporosity coefficient (αT) can be estimated from the thermal interporosity regime exhibited on the temperature derivative curve. The results also suggest that commercial geothermal energy harness is more difficult when the ωT is high or the αT is very small. Finally, we introduced an integrated workflow of combining PTA and TTA to characterize NFGRs. Simulated test examples are interpreted to demonstrate the applicability of the developed workflow. This work aids in better understanding the potentials of temperature data on geothermal reservoir characterization.

CHANGING WELLBORE STORAGE IN GAS WELL TESTING

Extended wellbore storage can be mistakenly interpreted as a reservoir response in gas well testing with surface shut in. This interpretation usually results in false value for permeability, skin and reservoir size and shape. This paper investigates changing wellbore storage in pressure transient testing with surface shut-in in gas well. This study was prompted by the observation, that in gas wells, many of the buildup tests obtained with surface shut-in exhibited complex reservoir model behavior with relatively low skin. The results presented in this paper are based on well test simulation and field data from North Sumatera. This work demonstrates the effect changing wellbore storage on the pressure derivative curve. Knowledge of the expected pressure derivative shape, and duration, will improve the design of buildup tests that will allow enough time for the actual reservoir response to be observed. This will result in a reliable reservoir model and correct estimation of permeability and skin factor.

Evolution of parameters in the Doyle-Fuller-Newman model of cycling lithium ion batteries by multi-objective optimization

An electrochemical model having high-fidelity parameters enables a correct description of the performance of lithium ion batteries. Hence, developing an accurate and high-efficiency parameter identification method is crucial to precisely predicting the battery’s state of health. In the past, most studies on estimation of such parameters took the discharge voltage as the only target to be fitted. Here, the first-order derivative of the discharge curve, i.e., the dQ/dV curve, is proposed as another fitting target since this new curve is directly related to battery aging. Four different objective functions, associated with the discharge curve and its derivative curve, are used to perform the multi-objective optimization, where the two algorithms, namely the genetic algorithm and the deep neural network are employed. We show that, by using the genetic algorithms, the mean absolute errors of the discharge curve for each cycle are lower than 0.07 (V), while the errors of the ICA curve are below 0.32 (Ah/V), both of which show a good convergence. The deep neural network also leads to excellent result. We present the evolutions of 13 identified parameters and demonstrate that the initial lithium ion concentration in the negative electrode dominates the cycle age of the tested batteries.

Well Test Analysis of Inclined Wells in the Low-Permeability Composite Gas Reservoir Considering the Non-Darcy Flow

The application of traditional well test interpretation methods cannot comprehensively consider characteristics of stress sensitivity and non-Darcy flow for low-permeability composite gas reservoirs, which makes it difficult to obtain real reservoir parameters. Based on the micro-mechanism analysis of stress sensitivity and non-Darcy flow in low-permeability gas reservoirs, the flow motion equation was improved. Thus, a mathematical model was established which belongs to the inclined well in the composite gas reservoir with a conventional internal zone and low-permeability external zone. Applying the finite element method to solve the flow model through Matlab programming, the equivalent pressure point was selected to research the pressure distribution of the inclined well. On this basis, the bottom hole pressure dynamic curve was drawn, the flow process was divided into seven stages, and the parameter sensitivity analysis was carried out. Finally, the advanced nature of the new model applied to the interpretation of the well test model is compared by conventional methods. The non-Darcy flow can cause the gradual upward warping of the bottom hole pressure dynamic curve in the later stage, and non-linear enhancement leads to an increase in the upturn through the simulation test. When the inclination angle is greater than 60°, early vertical radial flow and mid-term linear flow gradually appear. A decrease leads to a shorter duration of the pseudo radial flow in the internal zone and the radius of the internal zone. The conduction coefficients ratio of internal and external zones affects the pseudo pressure derivative curve slope in transition phase of pseudo radial flow in the internal and external zones. A comprehensive consideration of the low-permeability composite gas reservoir flow characteristics can improve the fitting degree of the pressure curves. Not only that, but it can also solve the strong diversification of reservoir parameters. Results have a guiding significance for low-permeability composite gas reservoir development and pressure dynamic evaluation in inclined wells.

Creatinine] can change in an unexpected direction due to the volume change rate that interacts with kinetic GFR: Potentially positive paradox.

[Creatinine] was proved to change in the opposite direction of the kinetic GFR (GFRK), but does the [creatinine] also change in the opposite direction of the volume rate? If volume is administered and the [creatinine] actually goes up, then the two changes move in the same direction and their ratio is positive, paradoxically. The equation that describes [creatinine] as a function of time was differentiated with respect to the volume rate. This partial first derivative has a global maximum that can be positive under definable conditions. Knowing what makes the maximum positive informs when the derivative will be positive over some continuous domain of volume rate inputs. The first derivative versus volume rate curve has a maximum and a minimum point depending on the GFRK. If GFRK is below a calculable value, then the curve's minimum vanishes, letting it descend to ‐∞ and not allowing the derivative to ever be positive. If GFRK lies between a lower and a higher calculable value, then the curve's maximum vanishes, letting the derivative diverge to +∞, though the clinical scenario is unrealistic. If GFRK is above the higher calculable value, then the curve's absolute maximum can become positive by decreasing the creatinine generation rate or increasing the initial [creatinine]. The derivative is potentially positive under these clinically realizable circumstances. The combination of parameters above can align in septic patients (low creatinine generation rate) with kidney failure (high initial [creatinine]) who are put on continuous dialysis (high GFRK). If a first derivative is positive, removing more volume can improve the [creatinine] and, dismayingly, giving more volume can worsen the [creatinine]. This paradox is explained by a covert interplay between the ambient [creatinine] and GFRK that excretes creatinine faster than its volume of distribution declines.

An analysis method of injection and production dynamic transient flow in a gas field storage facility

A dynamic transient flow analysis method considering complex factors such as the cyclic injection and production history in a gas field storage facility was established in view of the limitations of the existing methods for transient flow analysis and the characteristics of the injection-production operation of strongly heterogeneous gas reservoirs, and the corresponding theoretical charts were drawn. In addition, an injection-production dynamic transient flow analysis model named “three points and two stages” suitable for an underground gas storage (UGS) well with alternate working conditions was proposed. The “three points” refer to three time points during cyclic injection and production, namely, the starting point of gas injection for UGS construction, the beginning and ending points of the injection-production analysis stage; and the “two stages” refer to historical flow stage and injection-production analysis stage. The study shows that the dimensionless pseudo-pressure and dimensionless pseudo-pressure integral curves of UGS well flex downward in the early stage of the injection and production process, and the dimensionless pseudo-pressure integral derivative curve is convex during the gas production period and concave during the gas injection period, and the curves under different flow histories have atypical features. The new method present in this paper can analyze transient flow of UGS accurately. The application of this method to typical wells in Hutubi gas storage shows that the new method can fit the pressure history accurately, and obtain reliable parameters and results.

An approach for automatic parameters evaluation in unconventional oil reservoirs with deep reinforcement learning

Accurate estimation of unconventional reservoir parameters is of great significance to improve the development effect and prolong the life cycle of production wells. Reservoir parameter estimation based on pressure transient analysis (PTA) is a mainstream method due to its ease of use. However, the non-unique solution and human bias make the reliability of the method less than ideal. Therefore, a robust automatic interpretation method is urgently needed to alleviate these problems. In this work, we propose an automatic parameter evaluation method of unconventional reservoirs based on a combination of deep reinforcement learning (DRL) and PTA. Our key insight is to treat the PTA process, namely the pressure derivative curve matching process, as Markov decision process (MDP) and solve the optimal matching policy through DRL algorithm. Based on this idea, we trained an agent to automatically adjust the parameters of the trilinear flow model, a classic PTA model, and finally complete the pressure derivative curve matching to evaluate the unconventional oil reservoirs parameters. To make the training converge, branch deep Q-network with independent rewards strategy (IR-BDQ) was proposed to train the agent. Results show that IR-BDQ algorithm can effectively improve the convergence speed and parameter evaluation accuracy compared with other DRL algorithms. The results of 1000 curve matching tests showed that the mean average relative errors of parameters is 13.1%. In addition, comparison with the supervised learning algorithm reveals that the proposed method has the smallest variance of parameter inversion errors, indicating that the method has good robustness. Finally, the case study shows that the proposed method can effectively alleviate the non-unique solution problem, which is of great significance to improve the repeatability of parameter evaluation results in unconventional oil reservoirs.

Effects of water-soluble acrylic resin coatings on the pyrolysis behavior of wooden bulky waste

Water-soluble acrylic resin coatings (WSARC) are widely applied on wooden furniture surfaces. Moreover, the influence of WSARCs on the reaction mechanism and product properties during fast pyrolysis is critical to the resource disposal of wooden bulky waste. Herein, four samples, including plywood, primer coat paint, finish coat paint, and their mixture, were pyrolyzed and converted into bio-oil and bio-char. Gaussian curve fitting was applied to derivative thermogravimetric analysis curves to separate the reaction stages, and the Coats Redfern method was used to calculate the kinetic parameters during the devolatilization process of pyrolysis. The results showed that WSARCs changed the diffusion path of volatile and extended the entire devolatilization process. Although no significant difference was observed between the experimental and theoretical values in bio-char and bio-oil yield, the increase of the volatile residual time enhanced the secondary cracking/condensation of bio-oil, which decreased the oxygen containing components and increased fatty acid methyl esters/acid. Moreover, the overall devolatilization index D (5.48 × 10−6) was basically similar to the algebraic superposition result (5.11 × 10−6). Nevertheless, the overall apparent activation energy decreased from 85.9 to 60.1 kJ·mol−1 due to the enhancement of the volatile–char interaction.

Molecular identification and anti-malarial drug resistance profile of Plasmodium falciparum from patients attending Kisoro Hospital, southwestern Uganda

BackgroundThe evolution of malaria infection has necessitated the development of highly sensitive diagnostic assays, as well as the use of dried blood spots (DBS) as a potential source of deoxyribonucleic acid (DNA) yield for polymerase chain reaction (PCR) assays. This study identified the different Plasmodium species in malaria-positive patients, and the anti-malarial drug resistance profile for Plasmodium falciparum using DBS samples collected from patients attending Kisoro Hospital in Kisoro district, Southwestern Uganda.MethodsThe blood samples were prospectively collected from patients diagnosed with malaria to make DBS, which were then used to extract DNA for real-time PCR and high-resolution melting (HRM) analysis. Plasmodium species were identified by comparing the control and test samples using HRM-PCR derivative curves. Plasmodium falciparum chloroquine (CQ) resistance transporter (pfcrt) and kelch13 to screen the samples for anti-malarial resistance markers. The HRM-PCR derivative curve was used to present a summary distribution of the different Plasmodium species as well as the anti-malarial drug profile.ResultsOf the 152 participants sampled, 98 (64.5%) were females. The average age of the participants was 34.9 years (range: 2 months–81 years). There were 134 samples that showed PCR amplification, confirming the species as Plasmodium. Plasmodium falciparum (N = 122), Plasmodium malariae (N = 6), Plasmodium ovale (N = 4), and Plasmodium vivax (N = 2) were the various Plasmodium species and their proportions. The results showed that 87 (71.3%) of the samples were sensitive strains/wild type (CVMNK), 4 (3.3%) were resistant haplotypes (SVMNT), and 31 (25.4%) were resistant haplotypes (CVIET). Kelch13 C580Y mutation was not detected.ConclusionThe community served by Kisoro hospital has a high Plasmodium species burden, according to this study. Plasmodium falciparum was the dominant species, and it has shown that resistance to chloroquine is decreasing in the region. Based on this, molecular identification of Plasmodium species is critical for better clinical management. Besides, DBS is an appropriate medium for DNA preservation and storage for future epidemiological studies.

Self-Powered Sensing for Non-Full Pipe Fluidic Flow Based on Triboelectric Nanogenerators.

Fluidic flow monitoring of a non-full pipe is of great significance in the field of energy measurement and pipeline transportation. In this work, a monitoring method based on triboelectric nanogenerators for non-full pipe fluidic flow of large pipelines is proposed. Specifically, a triboelectric non-full pipe flow sensor (TNPFS) is fabricated, which can monitor the flow velocity and the liquid level simultaneously, and then the flow can be obtained by conversion. For flow velocity monitoring, the flexible blades slide between electrodes, generating periodic electrical signals. Interestingly, the frequencies of the voltage and flow velocities show a good linear relationship. For liquid level monitoring, according to the principle of liquid-solid contact electrification, a variable area interdigital electrode with a stable signal distributed on a polytetrafluoroethylene tube is designed. The experiments demonstrate that the peak number and trend of the voltage derivative curve are related to the liquid level. Finally, a real-time flow-monitoring system is established to effectively monitor the flow from 94 to 264 L/min. Compared with the actual measured flow, the error rate is under 1.95%. In addition to this, the TNPFS also has good responsiveness in sewage. This work provides a novel method for fluidic flow monitoring, especially the non-full pipe flow of large pipelines.

A novel pressure and rate transient analysis model for fracture-caved carbonate reservoirs

Fracture-caved carbonate reservoirs (FCCRs) have been developed worldwide and contribute significantly to world's hydrocarbon reserves. Numerous models for FCCRs were proposed in the previous works. However, with more and more exploitations, some kinds of FCCRs are observed from the field geological information but not reported in the existing literature. In this paper, a novel model for FCCRs is proposed and its corresponding pressure transient analysis (PTA) and rate transient analysis (RTA) solutions are presented. This model has a wider applicability than the previous models proposed by our research team. First, the geological model is established based on the geological information. Sequentially, the simplified physical model and the mathematical model are developed. Through Laplace transformation, Duhamel's principle, and Stehfest numerical inversion, the solutions of dimensionless bottom-hole pressure and dimensionless flow rate integral are derived. Then, the RTA type curves of two-cave model are plotted to recognize the flow characteristics, which can be divided into five regimes comprehensively. In addition, two concaves are observed on the derivative curve. The RTA type curves of three-cave model are also presented. A comparison between the RTA type curves of two-cave model and three-cave model shows that when one more cave exists in the formation, one more concave will be added to the derivative curve. Furthermore, the differences between the proposed model and previous models are presented through comparing the PTA type curves. Next, the effects of key parameters on the RTA curve behavior of two-cave model are demonstrated. Results indicate that the RTA curves are controlled by the friction and fluctuation coefficients, mobility, storage ratio, region radius, and cave storage constant. The friction and fluctuation coefficients influence the depth of first concave, while the storage ratio, region radius, and cave storage constant dominate the middle flow period, and the mobility has an impact on the boundary dominated flow regime. Finally, the application of proposed model on a field well from Shunbei Oilfield, western China is presented to calibrate its accuracy and reliability. ∙ A novel model for fracture-caved carbonate reservoirs is established. ∙The rate transient characteristics of this model is conducted. ∙Sensitivity studies of some key parameters on the pressure response are conducted. ∙An application of proposed model on a field well is presented.

An automated data-driven pressure transient analysis of water-drive gas reservoir through the coupled machine learning and ensemble Kalman filter method

Natural gas plays a crucial role in sustaining the economic development. The production behavior of natural gas reservoir is significantly affected by the connecting aquifer. To investigate the aquifer and reservoir properties, the pressure buildup well test is conducted and the pressure transient data need to be analyzed. However, the pressure transient data analysis usually involves a procedure to build an analytical or numerical model to predict the pressure transient dynamics. With the existence of many historical records on the well test data and advancement of machine learning method, a data-driven method is proposed here to automate the well test data analysis of water-drive gas reservoir. The dataset generated from the previous well test records is used as the training set for the machine learning method. To identify the water invasion mode, the random forest classification method is introduced, and the discrete linear segment slopes are extracted from the pressure derivative curve as the feature. To predict the pressure transient dynamics, the random forest regression method is proposed to construct a projection between the aquifer/reservoir properties and the pressure transient curves. Once the water invasion mode is determined and the data-driven model to predict the pressure transient dynamic is constructed, the ensemble Kalman filter is used to estimate the aquifer/reservoir properties from the well testing data. The results show that the random forest classification method can accurately identify the water invasion mode and the random forest regression based ensemble Kalman filter method can estimate the aquifer/reservoir properties accurately with the reduced uncertainty.

Pressure transient analysis of a multi-horizontal-well pad by a semi-analytical model: Methodology and case study

Drilling more infill multi-fractured horizontal wells (MFHWs) is one of the most direct oil and gas production methods in unconventional reservoirs with high recovery. MFHWs in the multi-horizontal-well pad can be easily interfered by the adjacent wells during well testing. Unfortunately, most of the existing well testing models for MFHWs are limited to a single well. A semi-analytical well testing model for transient pressure analysis in a multi-horizontal-well pad is presented in this work. In the proposed model, the entire formation is divided into three domains, namely matrix, natural fracture, and hydraulic fracture, to describe unconventional reservoirs comprehensively. With Laplace transform and Stehfest numerical inversion techniques, the reservoir models with matrix and natural fracture systems are solved analytically. The solutions of the hydraulic fracture model for multiple MFHWs are obtained by the finite difference method. The pressure superposition method and production rate relationship are used to characterize the impact from the adjacent wells. The general solutions of the multi-well reservoir model and hydraulic fracture model are then coupled to obtain the tested well's bottom-hole pressure. The results of the proposed model are in good agreement with the commercial numerical software. The multi-horizontal-well pad's integrated flow regimes can be divided into a bilinear flow, linear formation flow, the pseudo radial flow of hydraulic fracture, multi-MFHW effect, cross-flow between matrix and natural fracture, and formation pseudo radial flow. The pseudo radial flow of hydraulic fracture, the multi-MFHW effect, cross flow, and formation pseudo radial flow have unique characteristics in the multi-horizontal-well pad, and these flow regimes are highly affected by the adjacent MFHWs properties and well-spacing. With the change of well-spacing, the multi-MFHW effect is characterized by the linear flow inside the multi-horizontal-well pad or the multi-well pad's biradial flow. The comparison of pseudo-steady-state (PSS) flow and transient flow indicates that different cross-flow conditions from the matrix to natural fracture will only affect the derivative curve's cross-flow behavior. The case study shows that the proposed model can obtain a more accurate interpretation result of the tested well under the adjacent well's effect.

Pressure transient analysis for wells drilled into vertical beads-on-string caves in fracture-caved carbonate reservoirs: Field cases in Shunbei Oilfield

Tarim Basin, Western China has newly discovered fracture-caved carbonate reservoirs formed by large-scale fault tectonic activity and multiple-stage karstification. The large karst caves interconnecting with tectonic fractures in series to form vertical beads-on-string structure is one of the most common patterns. Moreover, the situations of wells drilled into caves often occur during drilling. The complex geological and engineering factors cause that traditional continuum-flow models are difficult to match the recorded pressure data. To present a novel well test model to reasonably estimate reservoir parameters, this work first presents a multi-cave multi-fracture series connection physical model by simplifying complex vertical beads-on-string structure. Four kinds of mediums are considered in physical model, including large caves, small vugs, high-angle tectonic fractures and rock matrix. Thereafter, the multi-cave-multi-region model for wells drilled into vertical beads-on-string caves is developed, among of which the flow in fracture regions obeys the Darcy's law, while the flow in large caves is assumed to obey free flow. Particularly, gravity effect is considered in fracture regions because the fluids flow along vertical structure. Then we analyze the typical flow regimes and conduct sensitivity analysis on crucial parameters. Results indicate that (a) the new cave storage regimes, characterized by unit-slope pressure-derivative curve, are recognized. This may help identify large karst caves in field case analysis; (b) The typical feature of vertical beads-on-string structure on type curves is that cave storage regimes and linear flow regimes alternately appear; (c) large cave and vug can be distinguished by the slope of pressure derivative on type curves; (d) gravity effect could lead to unit-slope pressure and pressure derivative curves, which is traditional recognized as the presence of a closed boundary when it may not be the case. Finally, three field cases from Shunbei Oilfield in which it is difficult to achieve good fitting quality using traditional models are interpreted to verify the practicability and feasibility of the proposed model.

Semianalytical model of complex fracture growth in vertical wells based on boundary element theory

The recent developments in low-permeability oil and gas reservoir mining technology have led to the application of various forms of well fracturing models to determine the physical formation parameters and flow laws in porous media. However, most related studies have been aimed at conducting a pressure transient analysis after the formation of fractures, ignoring the pressure change characteristics during fracture formation. In this study, a fracture growth model based on vertical fractured wells was established and solved using the source function theory and boundary element method. The rationality of the model calculation method was verified by the superposition principle. The pressure change laws before and after fracture growth were analyzed, and the model was subjected to hydraulic fracturing experiments. The results showed that with the increase in the local pressure at the bottom of the well, main fractures, branch fractures, and microfractures were generated in three stages. When the fracture was formed, the pressure and pressure derivative curves fluctuated but gradually returned to a stable state under the fracture shape with the extension of the flow time. Moreover, from the main fracture to the microfracture stage, the pressure recovery time period was gradually shortened. The fitting results of the analysis model and fracturing experiment were found to be accurate, providing a theoretical support for analyzing the transient pressure changes during the formation of complex fractures. The different curve characteristics also provide a new reference basis for evaluating the fracture propagation behavior and predicting the fracture conductivity.

The Pressure Buildup Well Test Analysis considering Stress Sensitivity Effect for Deepwater Composite Gas Reservoir with High Temperature and Pressure

Some deepwater gas reservoirs with high temperature and pressure have obvious stress sensitivity effect resulting in difficulty in well test interpretations. The influence of stress sensitivity effect on the pressure drawdown well test is discussed in many papers. However, the influence on the pressure buildup well test is barely discussed. For practices in oilfields, the quality of pressure data from the drawdown stage of well test is poor due to the influence of production fluctuation. Thus, the pressure data from the buildup stage is used for well test interpretations in most cases. In order to analyze the influence of stress sensitivity effect on the pressure buildup well test, this paper establishes a composite gas reservoir pressure buildup well test model considering the stress sensitivity effect and the hysteresis effect. Numerical solutions to both pressure drawdown and buildup well test models are obtained by the numerical differentiation method. The numerical solutions are verified by comparing with analytical solutions and the homogeneous gas reservoir well test solution. Then, the differences between pressure drawdown and buildup well test curves considering the stress sensitivity effect are compared. The parameter sensitivity analysis is conducted. Compared with the conventional well test curve, the pressure derivative curve of pressure drawdown well test considering the stress sensitivity effect deviates upward from the 0.5 horizontal line at the inner zone radial flow stage, while it deviates upward from the M/2 (mobility ratio/2) horizontal line at the outer zone radial flow stage. However, for the pressure buildup well test curve considering the stress sensitivity effect, the pressure derivative curve gradually descends to the 0.5 horizontal line at the inner zone radial flow stage, while it descends to the M/2 (mobility ratio/2) horizontal line at the outer zone radial flow stage. The pressure derivative curve of pressure buildup well test considering the hysteresis effect is higher than the curve without considering the hysteresis effect, because the permeability cannot be recovered to its original value in the buildup stage after considering the hysteresis effect. Meanwhile, skin factor and mobility ratio have different effects on pressure drawdown and buildup well test curves. Based on the model, a well test interpretation case from a deepwater gas reservoir with high temperature and pressure is studied. The result indicates that the accuracy of the interpretation is improved after considering the stress sensitivity effect, and the skin factor will be exaggerated without considering the stress sensitivity effect.

Production performance analysis of multi-fractured horizontal well in shale gas reservoir considering space variable and stress-sensitive fractures

Multi-stage fracturing technology makes shale gas production economically viable. In this paper, an innovative model incorporating space variable and stress-sensitive fractures is established for the production of MFHW in shale. Multi-transport mechanisms including Darcy flow, Knudson diffusion, Surface diffusion are considered in the mathematical model. Three space variable conductivity patterns (Linear, Exponential, and Logarithmic variations) are introduced and adopted. Based on the discretization method, a novel method is proposed which can simulate uniform and space varying fractures conveniently. Then the semi-analytical solution is obtained by Stehfest numerical inversion and an iteration method. And good agreements with previous models are observed in the validation. Afterward, the pressure transient type curve is generated and eight flow periods are identified. Subsequently, the influences of several vital parameters are discussed in detail. The results show that space varying fracture enlarges the pressure drop and decreases the productivity of early time. Such an effect is enhanced as the space variable coefficient is increased. And this influence decreases with the increase of initial conductivity. Considering stress-sensitive fractures, a ‘hump’ appears in the pressure derivative curve and the early time productivity decreases. A bigger stress-sensitive coefficient accelerates the appearance of the ‘hump’ and makes the ‘hump’ sharper. The ‘hump’ and productivity decline caused by dynamic conductivity becomes more obvious with the decrease of the minimum conductivity. Complex transport mechanisms enhance inter-porosity flow. The inter-porosity flow would appear earlier with complex transport mechanisms. The model can simulate the gas flow of MFHW more realistically. It can help for better understanding of the production dynamic of MFHW in shale. • A semi-analytical approach is established for the pressure and rate transient of MFHW in shale gas reservoir. • Space variable and stress-sensitive fractures and multi-transport mechanisms of shale gas are considered. • A new solution and an iteration method are utilized to solve the space varying fracture and nonlinear problem. • Effects of some vital parameters on production performance are analyzed.

Assessing the thermal and fungal behavior of eco-friendly epoxy thermosets derived from vegetable oils for wood protective coatings

The paper deals with the study of the obtaining, characterization and thermal and fungal behavior of a green thermoset based on epoxidized soybean oil (ESO), castor oil maleic anhydride adduct (COMA) and methyl nadic anhydride (MNA). By varying the MNA/COMA crosslinking agent ratio, resins with different degree of stiffness can be obtained suitable for green thermosets coatings. Differential scanning calorimetry (DSC) and a simultaneous TG/FT-IR/MS coupling were used to establish the crosslinking behavior, evolved gases analysis and thermal decomposition mechanisms associated with their corresponding kinetic parameters. The non–isothermal global kinetic parameters values (activation energy and pre–exponential factor) were calculated with the aid of the Friedman and Flynn–Wall–Ozawa isoconversional methods. The curves shape of the variation of activation energy versus conversion degree and first derivative (DTG) curves shapes suggest that the thermal degradation processes occurred in multi-step kinetics. Using a multivariate linear regression method the most probable thermal decomposition and crosslinking kinetic models were established. A good concordance between experimental and simulated data was obtained, confirming the correct description of the thermal mechanisms. The main identified gaseous fragments were water, carbon dioxide, saturated and unsaturated hydrocarbons and carboxylic derivatives. The decay resistance against two wood decaying strains, P. chrysogenum and A. brasiliensis was also evaluated.