Day 2 Wed, April 24, 2019最新文献

{"title":"Estimating Downhole Vibration via Machine Learning Techniques Using Only Surface Drilling Parameters","authors":"Prince Okoli, Juan Cruz Vega, R. Shor","doi":"10.2118/195334-MS","DOIUrl":"https://doi.org/10.2118/195334-MS","url":null,"abstract":"\u0000 Drillstring vibration can be divided into three types: axial, lateral and torsional. All three can cause significant wear and tear in drilling equipment, which leads to increased failures, non-productive time, and poor drilling performance. It also causes wasted mechanical energy and wellbore instabilities. Access to real-time, high-frequency downhole vibration data while drilling remains prohibitively expensive; however, it may be estimated via machine learning (ML) techniques using only surface drilling parameters. The task of predicting the severity of downhole vibration using surface parameters was approached as a supervised classification ML problem. Five basic, traditional techniques were investigated: the nearest neighbour, logistic regression, naïve Bayes, discriminant analysis, and decision trees.\u0000 Drilling data was obtained from multiple bottom hole assemblies (BHAs) from several wells in North America. The learning tasks were separated into inter-BHA runs (where the learner is trained on data from one BHA and tested with data from a different BHA) and intra-BHA runs (where the learner is trained and tested with data from the same BHA). Severity of vibration was assessed primarily through the time-weighted average of root mean square amplitude and then classed into severity levels. Performance of the classification results was assessed using the predictive accuracy and weighted macro-average of precision obtained using cross validation and presented as confusion matrices for specific iterations of the cross validation. The classification ML for the intra-BHA runs produced overall predictive accuracies that averaged between 50% and 85%. Of particular concern is the misprediction of certain vibration levels as either lower or higher levels, even when overall predictive accuracy is high.\u0000 The results show that these simple ML techniques can achieve considerable accuracy in the prediction of vibration levels for intra-BHA runs. For inter-BHA runs, predictive performance was reduced. This demonstration of the viability of ML in predicting bottom hole vibration motivates the application of more advance ML techniques, including deep learning estimators, and it signals the potential benefits that can be reaped.","PeriodicalId":425264,"journal":{"name":"Day 2 Wed, April 24, 2019","volume":"38 20","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113974845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Economic Nano-Additive to Improve Cement Sealing Capability","authors":"M. Tabatabaei, A. D. Taleghani, N. Alem","doi":"10.2118/195259-MS","DOIUrl":"https://doi.org/10.2118/195259-MS","url":null,"abstract":"\u0000 The primary objective of this study is introducing low-cost graphite nanoplatelets (GNPs) for oilwell cementing that improves long-term wellbore isolation and the durability of the hydrated cement. To seek this goal, we first propose two methodologies to modify the surface properties of the nano-additives to disperse them in the cement paste. There are essentially two significant incentives for the surface modification of nanoparticles: (1) a proper dispersion of nanoparticles in the slurry and (2) enhance the interaction between these nanoparticles and the cementitious matrix. It is expected that this interaction will improve the cement integrity by controlling micro-cracks initiation and their propagation. Then, experiments are conducted to assess enhanced mechanical behavior of the new cement nanocomposite.","PeriodicalId":425264,"journal":{"name":"Day 2 Wed, April 24, 2019","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121093359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Landing String Slip System Numerical Analysis to Evaluate Pipe Crushing Problems","authors":"Shailesh Mirasdar, K. Deshpande, Federico Amezaga","doi":"10.2118/195323-MS","DOIUrl":"https://doi.org/10.2118/195323-MS","url":null,"abstract":"\u0000 As the technology of offshore drilling improves, the industry seeks oil in deeper waters, inhospitable environments, and challenging climatic conditions. The new harsher drilling conditions warrant modifications to existing downhole tools and development of new technology using numerical simulations. The landing-string slip system (LSS) is a tubular-holding tool in which slips act as a spider to grip landing strings or drill pipe during makeup or breakout of drill strings. This paper presents a detailed numerical methodology to evaluate the safe pull-load rating for pipe held in the LSS. The method uses advanced computational techniques and applies ASME section VIII Division 2, Part 5 design criteria to corroborate numerical findings.\u0000 First, laboratory tests were conducted on pipes with varying sizes to estimate the pipe load-carrying capacity without causing operational failure. Strain gauge measurements were taken at regular intervals during the laboratory tests. A detailed finite element analysis (FEA) using an explicit solver was conducted to computationally simulate the LSS operating mechanism. In particular, non-linear FEA was conducted on the 45° pipe section to simulate slip indentations followed by axial loading of the pipe. The maximum axial load applied on the pipe after slip indentation corresponds to 100% yielding load. ASME Section VIII Division 2, Part 5 design criteria involving ratcheting analyses was applied towards numerical studies at a 100% yield loading condition.\u0000 Extensive FEA studies were conducted to check the validity of the numerical results with laboratory testing and then to understand the LSS capabilities for field-based loading scenarios. FEA studies predicted stresses within 10% of the values obtained through laboratory measurements. Simultaneously, FEA plastic strain patterns revealed that the spread of plastic strains is highly localized to the penetrated surfaces of the pipe and is also generally absent through the thickness for load capacity up to 100% of the pipe yield strength. Based on ASME section VIII Division 2, Part 5, a ratcheting analysis was conducted that involved loading and unloading cycles on the pipe to monitor the plastic strain propagation. The ratcheting analysis determined that for a 90% yield load, the LSS safely held pipe for operational purposes.\u0000 The ratcheting evaluation was not possible using laboratory tests because of the cost and time required for a cyclic loading test. This paper introduces ASME section VIII Division 2, Part 5 design criteria to develop confidence in numerical results and justify the LSS design.","PeriodicalId":425264,"journal":{"name":"Day 2 Wed, April 24, 2019","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121208793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Revisiting Kelvin Equation for Accurate Modeling of Pore Scale Thermodynamics of Different Solvent Gases","authors":"Ilyas Al-Kindi, T. Babadagli","doi":"10.2118/195319-MS","DOIUrl":"https://doi.org/10.2118/195319-MS","url":null,"abstract":"\u0000 Understanding the thermodynamics of fluids in capillary media is essential to achieve a precise modeling of EOR applications such as hybrid (with thermal methods) and sole solvent injection processes. The theoretically derived classical Kelvin equation describes the influence of surface tension, contact angle, pore radius, and temperature on vapour pressures. The deviation of propane vapour and condensation pressures from this equation was determined experimentally by measuring them on capillary/porous media with various sizes and types, namely Hele-Shaw glass cells, silica-glass microfluidic chips, and rock samples. The experimental data were also compared with the vapour pressures obtained for the bulk conditions. The gap thicknesses in Hele-Shaw cells were 0.13 and 0.04 mm whereas the medium size in micromodels was ranging from 142 to 1μm. The results showed that vapour and condensation pressures of propane recorded in the experiments were comparatively close to the bulk vaporization pressure and calculated vapour pressures from the Kelvin equation. Conversely, vapour pressures obtained from rock samples were noticeably lower than bulk vapour pressures.","PeriodicalId":425264,"journal":{"name":"Day 2 Wed, April 24, 2019","volume":"21 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123222140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of Gas and Downhole Water Sink-Assisted Gravity Drainage GDWS-AGD Process in Saturated Oil Reservoirs with Infinite-Acting Aquifer","authors":"Dahlia A. Al-Obaidi, W. Al-Mudhafar, A. Wojtanowicz, M. Al-Jawad, D. Saini","doi":"10.2118/195332-MS","DOIUrl":"https://doi.org/10.2118/195332-MS","url":null,"abstract":"\u0000 A hybrid Gas-Enhanced and Downhole Water Sink-Assisted Gravity Drainage (GDWS-AGD) process has been suggested to enhance oil recovery by placing vertical injectors for CO2 at the top of the reservoir with a series of horizontal oil-producing and water-drainage wells located above and below the oil-water contact, respectively. The injected gas builds a gas cap that drives the oil to the (upper) oil-producing wells while the bottom water-drainage wells control water cresting. The hybrid process of GDWS-AGD process has been first developed and tested in vertical wells to minimize water cut in reservoirs with bottom water drive and strong water coning tendencies. The wells were dual-completed with 7-inch production casing and 2-3/8 inch tubings and perforated above the oil-water contact (OWC) for oil production and below OWC for water drainage. The two completions were hydraulically isolated inside the well by a packer. The bottom (water sink) completion drained water with a submersible pump.\u0000 The GDWS-AGD was efficiently adopted to improve oil recovery at the PUNQ saturated oil field. The PUNQ Field has an infinite active aquifer with very strong edge and bottom water drives. A black oil reservoir flow model was implemented for CO2 flooding simulation of the GDWS-AGD process in comparison with the Gas-Assisted Gravity Drainage (GAGD) process. The comparison was performed to obtain the clearest image about the performance of the combined GDWS-AGD process. Next, Design of Experiments (DoE) and proxy modeling were incorporated to find the most sensitive parameters that affect the GDWS-AGD process performance. The candidate parameters are porosity, horizontal and vertical permeability for each layer, radius of aquifer and rock compressibility.\u0000 In the GDWS-AGD, the produced water not only reduced water cut and coning, but also significantly reduced the reservoir pressure, resulting in improving gas injectivity. In addition, the GDWS-AGD process improved cumulative oil production. More specifically, the results showed that cumulative oil production increased from 3.8*105m3 to 4.7*105m3 and water cut decreased from 97% to 92% in all the horizontal oil producers. For the proxy model, it was cleared from Sobol analysis that the porosity for layer 5 was more influential parameter than others on cumulative oil through GDWS-AGD process with 31% main effects and 0.025% interaction effects, while the horizontal permeability for layer 4 was the most influential parameter with 24% main effects and 1.5% interaction effects. The novelty of GDWS-AGD process comes from its effectiveness to improve oil recovery with reducing the water coning, water cut, and improving gas injectivity. This leads to more economic implementation, especially with respect to the operational surface facilities.","PeriodicalId":425264,"journal":{"name":"Day 2 Wed, April 24, 2019","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129016236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Digital Solutions to Optimize Jet Pump Technology for Production Enhancement","authors":"K. Deshpande, Michael Knoeller, V. Patkar","doi":"10.2118/195261-MS","DOIUrl":"https://doi.org/10.2118/195261-MS","url":null,"abstract":"\u0000 Artificial lift systems provide a reliable means for ensuring production through depleted wells. Traditional artificial lift technology is seriously challenged and has shown faster wear in tough operating environments at greater depths, high dog leg severities and multi-phase fluid environment. Jet pump technology with no moving parts and compact design is an excellent alternative for production enhancement in most challenging downhole conditions. In this paper digital computational fluid flow analysis is conducted to optimize the jet pump design to improve operational life of the jet pump and reduce non-productive time (NPT). Comprehensive laboratory testing is conducted and digital solutions are compared against the test data to validate the new jet pump technology.\u0000 The operation of jet pump starts with flow of high pressure power fluid from surface into wellbore that travels through jet pump nozzle causing reduction in pressure which in turn draws in the reservoir fluid into jet pump throat. The low pressure generated at throat due to venturi effect can cause cavitation in certain scenarios and leads to reduced operational life of jet pump. To address this issue an alternative inverse jet pump is proposed that reverses the flow path of power fluid and production fluid. Numerical analysis is conducted to evaluate the feasibility of inverse jet pump design. Three-dimensional computational fluid dynamics (CFD) simulations are conducted using coupled algorithm with Reynolds-Averaged Navier-stokes (RANS) equation and k-ε turbulence model to predict the pressure and velocity flow field. Extensive laboratory testing is conducted in flow loop for the inverse jet pump design to validate the digital analysis results.\u0000 CFD simulations are performed for different configurations of inverse jet pump by varying throat diameter and length of mixing chamber for operating production and power fluid flow rates. CFD results underscored the pressure and velocity profiles along the flow paths and based on digital analysis using CFD it is observed that innovative inverse jet pump design reduces probability of cavitation. Laboratory testing corroborated with digital analysis results and indicated improvement in operational life for inverse jet pump technology. Extensive usage of advanced computational modeling in this work assisted in optimizing design quickly and reduced time and cost associated with laboratory testing. This work elucidates use of digital solutions for design optimization of new production technology and underscores simulation-based-design as faster and cost effective method.","PeriodicalId":425264,"journal":{"name":"Day 2 Wed, April 24, 2019","volume":"240 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116361556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Active Cooling Method for Downhole Systems in High Temperature Environment","authors":"Wenkai Gao, L. Ke, Yinao Su, Limin Sheng, Cao Chong, Xiurong Dou, Lei. Zhang","doi":"10.2118/195353-MS","DOIUrl":"https://doi.org/10.2118/195353-MS","url":null,"abstract":"\u0000 With the further exploration of oil and gas, we have to search for new resources which buried in deep strata, and most of the deep and ultra-deep wells are categorized in high-pressure/high-temperature (HPHT) wells. The problem of high temperature and the challenge to the existing downhole equipments are becoming increasingly prominent, where the drilling depth is severely restricted. Most of the HPHT or ultra-HPHT wells with reservoir temperature about 175~220°C would be drilled with near-bit measurement and constructed. In such a temperature environment, the conventional measurement while drilling tools with common electronics will experience very high failure rates at these conditions.\u0000 There are two ways to deal with the downhole electronics system in HPHT wells. One technique is called the passive cooling, which aims to improve the anti-temperature performance of the components and add thermal insulation materials to the circuit module. In this way, the cost of the instruments would be greatly increased, and the capacity for anti temperature could not be improved indefinitely, especially in HPHT or ultra-HPHT environment for lone period. The other solution is called the active cooling, which commit to the construction of a downhole refrigeration system. The cooling system power by bettery or downhole generator ensures clectronics cabin always under suitable temperature.\u0000 According to a large number of research work by scholars worldwide, there are 2 main kinds of downhole active cooling techniques suitable for while-drilling environment. One is thermoelectric based regeneratiove cooling system, and the other technique is based on regenerative cryogenic refrigeration cycle. The thermodynamic cycle and working fluid are key concerns for the refrigeration. While reverse-Brayton cycle contains adiabatic compression, isobaric heat transfer, adiabatic expansion and isobaric heat transfer, so thermoacoustic coolers, stirling cryocoolers, and pulse tube refrigerators can all be suitable solution.\u0000 The study from this work demonstrates the active cooling method for downhole systems using in high-temperature environment, and provides a baseline framework for design methods. The preliminary laboratory test and application showed the feasibility of the method.","PeriodicalId":425264,"journal":{"name":"Day 2 Wed, April 24, 2019","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131235665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving Water Efficiency in the Wilmington Field Using Streamline-Based Surveillance","authors":"Ryan R. Kwong, Ryan P. Kellogg, M. Thiele, Dave Simmons","doi":"10.2118/195372-MS","DOIUrl":"https://doi.org/10.2118/195372-MS","url":null,"abstract":"\u0000 This paper describes application of a streamline-based surveillance methodology to define injector-centered-patterns using streamlines, calculate pattern efficiencies, and propose target rates for injectors and producers to improve oil production, lower WOR, and reduce water cycling in the Wilmington Field.\u0000 The Wilmington Field is a faulted anticline structure in the Los Angeles Basin with alternating sand/shale sequences, which straddles offshore and onshore locations in Long Beach, California. It has been actively waterflooded since 1953 and currently injects over 1.6 million barrels of water injected (BWIPD) and produces at ~98% water cut. Due to the industrial port environment and history of subsidence, a minimum voidage replacement ratio (VRR) is required to sustain stable surface elevations. Given the scale of the Wilmington field, we focused on implementing two pilots to improve the flood performance by targeting different fault blocks/reservoirs: Fault Block 2 Tar Reservoir (Tar 2) and Fault Block 7 Ranger Reservoir (Ranger 7) which together represent 5% of total Wilmington oil production. Both surveillance models used a multi-layered numerical grid with geologic properties from existing 3D geomodels. The key objective for Tar 2 and Ranger 7 was to redistribute the current injected water volumes to improve oil production while maintaining VRR targets. Injection into the Tar 2 model was vertically refined to per-sand using pseudo-injectors in the modeling approach. Injection wells for the Ranger 7 model used a single path and injection volumes were allocated into each sand using permeability-height (kh) values. Rate changes suggested by the surveillance model for both pilot areas were made through choke adjustments and/or well shut-ins and required no pump size changes or workovers.\u0000 The Tar 2 and Ranger 7 pilots were monitored over a 6-month and 17-month period, respectively. The Tar 2 pilot area resulted in a decrease from 20% to 2 % annual oil decline rate while keeping a constant injection rate, while the Ranger 7 pilot area new rate target resulted in WOR from 52 to 47 and a decrease in annual oil decline from 15% to 5%. With the success of the waterflood management approach seen in Tar 2 and Ranger 7, a larger area in the Wilmington Field, Fault Block 6 Ranger (23% of total production) is now under a similar evaluation with the goal of reducing WOR and oil decline using the same surveillance methodology.","PeriodicalId":425264,"journal":{"name":"Day 2 Wed, April 24, 2019","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132330496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Event Recognition on Time Series Frac Data Using Machine Learning","authors":"A. Ramirez, J. Iriarte","doi":"10.2118/195317-MS","DOIUrl":"https://doi.org/10.2118/195317-MS","url":null,"abstract":"\u0000 Hydraulic fracturing pumping data is recorded and mapped in the field at one-second intervals. The designation of the stage start and end time is very important because these boundaries govern summary calculations, such as pressure, rate, and concentrations. Manual selection of staging flags is often very time consuming and prone to inaccuracies due to the lack of uniform selection and interpretation methods across the industry. The purpose of this study is to demonstrate the automation process to identify accurate and consistent stage start and end times in a high-frequency treating plot using machine learning algorithms.\u0000 This study is based on the analysis of metered high-frequency treatment data coupled with supervised machine learning algorithms. The pumping dataset includes treating pressure, slurry rate, and clean volume for 179 stages, for a total of 1,530,445 rows of data per variable. Sixty-six percent of the data were used to train the model, eight percent were used to validate the model, and the remaining twenty-six percent were used to test it. Subject matter expertise, taking into account user-defined start/end time flags, was used to train the algorithm.\u0000 Pumping data behaves very differently than traditional time-series data such as weather, stock prices, or population growth. The features examined are not affected by time but by physical events, so the correlation or dependency between features can affect accurate pattern recognition. To allow the algorithm to run leaner, the dataset was pre-processed using loss functions, smoothing techniques, and the rate of change of the main data channels. To understand how data may impair the predictions and to evaluate different model performances, we tested two classification algorithms: logistic regression and support vector machine.\u0000 Classification techniques were used to generate an accurate suggestion of where the pumping of a hydraulic fracturing stage starts and ends in a high-frequency treating plot. Results show that flag predictions have a training and validation accuracy of approximately 90 percent using logistic regression algorithms. The predicted flags were within 10 seconds of the manual selected flag. A limitation of this method is that it requires periodic retraining with new field data to improve the prediction robustness and to maintain high accuracy.\u0000 Accurate start and end time selections make it not only viable to process large volumes of fracture treatment data but also reduce the time spent reviewing field data for quality control. Petroleum engineers need to continue their focus on optimizing their systems with the greatest possible efficiency. Leveraging common analytical methods combined with the large, structured datasets that are readily available provide impressive results without extensive programming knowledge.","PeriodicalId":425264,"journal":{"name":"Day 2 Wed, April 24, 2019","volume":"217 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122925061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characterizing of Ferric Ion interaction with Viscoelastic Surfactant VES-Based Acidizing Fluid","authors":"S. Afra, H. Samouei, H. Nasr-El-Din","doi":"10.2118/195373-MS","DOIUrl":"https://doi.org/10.2118/195373-MS","url":null,"abstract":"\u0000 Viscoelastic surfactant (VES) have been successfully applied as acid-diversion fluids. However, high temperature, interaction of VES and Fe(III), addition of alcohol-based additives, and chelating agents all interfere with the apparent viscosity of the VES-based acid and reduce its efficiency. In the present study, the interactions of Fe(III) with a new type of VES-based acid system, which can be applied effectively for diversion at high temperatures, were characterized in a wide range of pH.\u0000 The physical behavior of the VES solutions after addition of iron at various pH values were observed visually to determine any change in the viscoelasticity of the solutions. In the present study, because of the similarity between chemical structures, 3-sulfopropyldimethyl-3-methacryl -amidopropylammonium (SMA) was used as a model compound of VES to characterize the nature of the interaction between VES and Fe(III). IR spectroscopy was employed to understand the nature of the SMA interactions with Fe(III) in different pH values. Also, UV-vis spectroscopy was conducted to determine stoichiometry of the interactions as well. Single X-ray crystallography was also utilized to further understand the nature of interaction between SMA and Fe(III).\u0000 Bottle test results show the formation of a viscoelastic gel at different pH in the presence of Fe(III)and VES. IR results express that the interaction of SMA and Fe(III) occurs through the amide group in the SMA which is existed in the headgroup of tested VES too. These results confirms previous observations that the interaction of amide part of the VES with Fe(III) results in screening the repulsion forces between surfactant head groups and formation of wormlike micelles that is the primary reason for increase in the viscosity. Results of continuous variation method on SMA and Fe(III) also confirm the 1:1 stoichiometry in their interaction which are in agreement with the results of our previous study on stoichiometry of VES and Fe(III) interaction.\u0000 The present paper is the first mechanistic attempt to characterize and understand the nature of a VES-based system interaction with Fe(III) by using a model compound that has the same headgroup as tested VES. The findings of the present study can be utilized to further investigations of the effects of additives on the performance of VES- based systems.","PeriodicalId":425264,"journal":{"name":"Day 2 Wed, April 24, 2019","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123162925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}