Petrus In ‘T Panhuis, S. Mahajan, C. Prin, Ahmed Al Ajmi
{"title":"Impact of Static and Dynamic Wellbore Strengthening on Well Planning in Petroleum Development Oman","authors":"Petrus In ‘T Panhuis, S. Mahajan, C. Prin, Ahmed Al Ajmi","doi":"10.2118/207239-ms","DOIUrl":"https://doi.org/10.2118/207239-ms","url":null,"abstract":"\u0000 Formation Integrity Tests (FIT) or Leak-Off Tests (LOT) are common techniques to reduce the uncertainty in Fracture Gradient (FG) prediction for well planning, but are usually performed at the casing shoe. This article will discuss the first examples of open-hole LOT and FIT in Petroleum Development Oman (PDO), targeting depleted formations in water injector or oil producer wells. The data was used to justify continued drilling of slim wells with two casing strings, where otherwise three casing strings would be required, provided dynamic wellbore strengthening is applied.\u0000 In addition, the concept of static wellbore strengthening was also trialed for the first time in Oman, using the hesitation squeeze testing procedure, by which the effective leak-off pressure was incrementally increased to match the maximum ECD required for cementing.","PeriodicalId":10981,"journal":{"name":"Day 4 Thu, November 18, 2021","volume":"73 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86138604","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":"What the Shale are We Talking About!","authors":"B. Hoxha, C. Rabe","doi":"10.2118/207412-ms","DOIUrl":"https://doi.org/10.2118/207412-ms","url":null,"abstract":"\u0000 Shale ‘stability’ has been extensively studied the past few decades in an attempt to understand wellbore instability problems encountered while drilling. Drilling through shale is almost inevitable, it makes up 75 percent of sedimentary rocks. Shale tends to be characterized as having high in-situ stresses, fissile, laminated, with low permeability. However, not all shale are the same, and the problem herein lies where they are all treated as such, in which most cases, has shown to be ineffective. Ironically, shale is predominantly generalized as being \"reactive/swelling\". Even though this can be true, it is not always the case because not all shale is reactive! In reality, there are many different types of shale: ductile, brittle, carbonaceous, argillaceous, flysch, dispersive, kaolinitic, micro-fractured etc. This study aims to clear many misconceptions and define different types of shale (global case scenarios) and their failing mechanisms that lead to wellbore instability, formation damage and high drilling cost. Afterwards, solutions will be offered, from a filed operation perspective, which will provide guidelines for stabilizing various shale based on their failure mechanism. Furthermore, we will define the symptoms for shale instability and propose industry accepted remedies.","PeriodicalId":10981,"journal":{"name":"Day 4 Thu, November 18, 2021","volume":"30 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86265190","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":"Tanks Assurance and Endorsement Extension Strategy","authors":"Sahar Abdul-Karim Khattab, Marwa Sami Alsheebani","doi":"10.2118/207694-ms","DOIUrl":"https://doi.org/10.2118/207694-ms","url":null,"abstract":"\u0000 The objective of this paper is to study various methods that can be implemented on existing or new tanks to achieve an extended endorsement period (e.g. 20 years plus) for Crude Oil Floating Roof Storage Tanks. This extended period is necessary in order to overcome anticipated future challenges in tank availability due to (i) increased production and loading, (ii) stretched major overhaul (MOH) duration due to unforeseen delays in MOH works, (iii) corrosion in bottom plates, etc. An extensive research based on international API Standard 653 \"Tank Inspection, Repair, Alteration, and Reconstruction\" was conducted to achieve this extended period. Initially, some COS tanks aspects were assessed based on API SPEC 653 (2014, Addendum 2, May 2020) to achieve this new Tanks Endorsement Vision, such as: (a) studying the currently applied Corrosion Protection Barriers to the COS tanks and their effectiveness to the endorsement period, (b) the adequacy of commonly applied Corrosion Protection Barriers with respect to the endorsement period, and (c) exploring possible enhancements on COS Tanks Corrosion Protection Barriers, and Monitoring systems to extend tanks endorsement period. Based on API SPEC 653 (2014, Addendum 2, May 2020), currently applied tank safeguards were found inadequate to achieve the 20 years plus tank endorsement period requirement. In order to extend tanks endorsement period, additional safeguards shall be implemented, with special attention to tank bottom plates (soil side), since corrosion problems are mostly exhibited in tank bottom plates from the soil/oil side. Multiple solutions for corrosion safeguards were explored and recommended as part of this study such as the installation of a CP system under COS tanks, as well as installation of a corrosion monitoring system, and performing routine in-service inspections for COS tanks (internal and external) as per API SPEC 653 (2014, Addendum 2, May 2020), etc. Overall, this paper provides an insight on the calculation method of tanks endorsement period, and possible tank corrosion safeguards and controls that can be implemented to extend the COS tanks endorsement period to at least 20 years. Results and recommendations studied in this paper will benefit the Oil and Gas Industry and help in overcoming future challenges.","PeriodicalId":10981,"journal":{"name":"Day 4 Thu, November 18, 2021","volume":"710 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74762257","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}
F. Zausa, L. Besenzoni, Alessandro Caia, Seda Mizrak
{"title":"Quantitative Evaluation of Well Blowout Risk and Oil Spill Mitigation Measures","authors":"F. Zausa, L. Besenzoni, Alessandro Caia, Seda Mizrak","doi":"10.2118/207962-ms","DOIUrl":"https://doi.org/10.2118/207962-ms","url":null,"abstract":"\u0000 The disaster of Macondo of 2010 changed the rules in reliability and safety standards during drilling operations. New regulations were developed in order to improve the control level on blowout risk, and all upstream operators adopted innovative technologies capable to reduce the potential risk of uncontrolled release, either by decreasing its frequency of occurrence or the expected impacts. The objective of this paper is to present a Quantitative Risk Analysis (QRA) of well blowout and measure the beneficial contribution of intervention technologies in terms of expected reduction of spill volume and associated costs.\u0000 The QRA is applied to any kind of well operation (drilling, completion, workover, light intervention) and well type. The methodology relies upon different risk analysis techniques able to quantify the residual blowout risk, as well as the mitigation provided by each technology. Through Fault Tree Analysis (FTA), a value of blowout probability is calculated for each well operation. The initial blowout condition is associated with a blowout flow rate, calculated with fluid dynamic computational models depending on well flow path and release point into the environment. The evolution of each release scenario is then studied with the use of Event Tree Analysis (ETA), where a set of events, able to reduce or stop the flow, are considered with their probability of success and occurrence time (well bridging, water coning, surface intervention through killing/capping techniques, relief well operations). The value of each intervention is estimated through Decision Tree Analysis (DTA), calculating the amount of spill volume reduction and avoided spill costs.\u0000 Results of spill volume and cost reduction are calculated for a set of specific wells, considering the application of killing/capping systems as well as Eni innovative technologies. The benefit of these interventions is measured in terms of Expected Monetary Value (EMV) in relation to a potential release extinguished by a relief well, which is the decisive intervention to stop the blowout, considered as the worst case scenario. Surface interventions with killing/capping techniques are the major contributors to the reduction of blowout impacts, and all additional measures which can be adopted should act in the fastest way possible before the arrival of heavy capping stack system.\u0000 The main innovative contribution of the proposed QRA methodology is the association of an expected economic value to post-blowout mitigation techniques, which takes into account all possible uncertainties related to their success and intervention time. Moreover, by evaluating an economic impact of the residual spill cost, it is possible to prioritize and increase the overall efficiency of the oil spill response plan for each operational and geographical context, and improve the control on blowout risk mitigation process.","PeriodicalId":10981,"journal":{"name":"Day 4 Thu, November 18, 2021","volume":"489 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77054725","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}
Salah Bahlany, Mohammed Maharbi, Saud Zakwani, F. Busaidi, Ferrante Benvenuti
{"title":"STEP Change in Preventing Stuck Pipe and Tight Hole Events Using Machine Learning","authors":"Salah Bahlany, Mohammed Maharbi, Saud Zakwani, F. Busaidi, Ferrante Benvenuti","doi":"10.2118/207823-ms","DOIUrl":"https://doi.org/10.2118/207823-ms","url":null,"abstract":"\u0000 Wellbore stability problems, such as stuck pipe and tight spots, are one of the most critical risks that impact drilling operations. Over several years, Oil and Gas Operator in Middle East has been facing problems associated with stuck pipe and tight spot events, which have a major impact on drilling efficiency, well cost, and the carbon footprint of drilling operations. On average, the operator loses 200 days a year (Non-Productive Time) on stuck pipe and associated fishing operations.\u0000 Wellbore stability problems are hard to predict due to the varying conditions of drilling operations: different lithology, drilling parameters, pressures, equipment, shifting crews, and multiple well designs. All these factors make the occurrence of a stuck pipe quite hard to mitigate only through human intervention.\u0000 For this reason, The operator decided to develop an artificial intelligence tool that leverages the whole breadth and depth of operator data (reports, sensor data, well engineering data, lithology data, etc.) in order to predict and prevent wellbore stability problems.\u0000 The tool informs well engineers and rig crews about possible risks both during the well planning and well execution phase, suggesting possible mitigation actions to avoid getting stuck. Since the alarms are given ahead of the bit, several hours before the possible occurrence of the event, the well engineers and rig crews have ample time to react to the alarms and prevent its occurrence.\u0000 So far, the tool has been deployed in a pilot phase on 38 wells giving 44 true alarms with a recall of 94%. Since mid-2021 operator has been rolling out the tool scaling to the whole drilling operations (over 40 rigs).","PeriodicalId":10981,"journal":{"name":"Day 4 Thu, November 18, 2021","volume":"27 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80196095","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":"Transformer-Based Deep Learning Models for Well Log Processing and Quality Control by Modelling Global Dependence of the Complex Sequences","authors":"Ashutosh Kumar","doi":"10.2118/208109-ms","DOIUrl":"https://doi.org/10.2118/208109-ms","url":null,"abstract":"\u0000 A single well from any mature field produces approximately 1.7 million Measurement While Drilling (MWD) data points. We either use cross-correlation and covariance measurement, or Long Short-Term Memory (LSTM) based Deep Learning algorithms to diagnose long sequences of extremely noisy data. LSTM's context size of 200 tokens barely accounts for the entire depth. Proposed work develops application of Transformer-based Deep Learning algorithm to diagnose and predict events in complex sequences of well-log data.\u0000 Sequential models learn geological patterns and petrophysical trends to detect events across depths of well-log data. However, vanishing gradients, exploding gradients and the limits of convolutional filters, limit the diagnosis of ultra-deep wells in complex subsurface information. Vast number of operations required to detect events between two subsurface points at large separation limits them. Transformers-based Models (TbMs) rely on non-sequential modelling that uses self-attention to relate information from different positions in the sequence of well-log, allowing to create an end-to-end, non-sequential, parallel memory network. We use approximately 21 million data points from 21 wells of Volve for the experiment.\u0000 LSTMs, in addition to auto-regression (AR), autoregressive moving average (ARMA) and autoregressive integrated moving average (ARIMA) conventionally models the events in the time-series well-logs. However, complex global dependencies to detect events in heterogeneous subsurface are challenging for these sequence models. In the presented work we begin with one meter depth of data from Volve, an oil-field in the North Sea, and then proceed up to 1000 meters. Initially LSTMs and ARIMA models were acceptable, as depth increased beyond a few 100 meters their diagnosis started underperforming and a new methodology was required. TbMs have already outperformed several models in large sequences modelling for natural language processing tasks, thus they are very promising to model well-log data with very large depth separation. We scale features and labels according to the maximum and minimum value present in the training dataset and then use the sliding window to get training and evaluation data pairs from well-logs. Additional subsurface features were able to encode some information in the conventional sequential models, but the result did not compare significantly with the TbMs. TbMs achieved Root Mean Square Error of 0.27 on scale of (0-1) while diagnosing the depth up to 5000 meters.\u0000 This is the first paper to show successful application of Transformer-based deep learning models for well-log diagnosis. Presented model uses a self-attention mechanism to learn complex dependencies and non-linear events from the well-log data. Moreover, the experimental setting discussed in the paper will act as a generalized framework for data from ultra-deep wells and their extremely heterogeneous subsurface environment.","PeriodicalId":10981,"journal":{"name":"Day 4 Thu, November 18, 2021","volume":"38 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82930398","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}
G. Wang, Dexiang Duan, Wanjun Li, Feng Qian, Zheng Qin, Zhao Zhong, Chuan Zhou, Baletabieke Bahedaer, Ning Jing, D. Ye, Qingyun Gao, Yue Xiao, Ganlu Li, Jitong Liu, Guobin Zhang, Shaohua Li
{"title":"Research and Application of Micro-Expansion and Anti-Channeling Cement Slurry System in Agadem Oilfield","authors":"G. Wang, Dexiang Duan, Wanjun Li, Feng Qian, Zheng Qin, Zhao Zhong, Chuan Zhou, Baletabieke Bahedaer, Ning Jing, D. Ye, Qingyun Gao, Yue Xiao, Ganlu Li, Jitong Liu, Guobin Zhang, Shaohua Li","doi":"10.2118/207592-ms","DOIUrl":"https://doi.org/10.2118/207592-ms","url":null,"abstract":"\u0000 The overall liner cementing qualification rate is only 40% in Agadem block of Niger, The cement slurry system used in the field has a UCA transition time of 43min, and an expansion rate of -0.03% in 24h, which result in a poor anti-gas channeling performance. The expansive agent and the anti-gas channeling toughening agent of anti-channeling agent were optimized through experiment study. A novel micro-expansion anti-gas channel cement slurry system which is suitable for Agadem block was obtained through experiment optimization study: 100% G +2 ∼ 4% fluid loss agent +3 ∼ 4.5% anti-channeling agent +1 ∼ 2% expansion agent-100S +0.15 ∼ 0.4% retarder +0 ∼ 0.3% dispersant +0 ∼ 0.25% defoamer + water. This new cement system has a good anti-gas channeling performance, the cement strength is 24.5-35.0MPa after 24hrs, the UCA transition time is 16-18min, and the expansion rate is 1.5-1.7%. At the same time, a cementing prepad fluid suitable for the block and the micro-expansion cement slurry system is selected to ensure the performance of the cement slurry's anti-channeling performance. The field test results proofs the good performance of the new cement system. The cementing qualification rate of Koulele W-5 well is 96%, and the second interface cementation is Good. The cementing qualification rate of Trakes CN-1 well is 100% which second interface cementation is Excellent. This paper has positive guidance and reference for cementing in Agadem block.","PeriodicalId":10981,"journal":{"name":"Day 4 Thu, November 18, 2021","volume":"90 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80294770","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}
Nasser AlAskari, Muhamad Zaki, Ahmed Aljanahi, Hamed AlGhadhban, E.A.E. Ali, V. Stashevsky
{"title":"Artificial Lift Optimization for Shallow Carbonate Magwa and Ostracod Formations with Massive Propped Fractures","authors":"Nasser AlAskari, Muhamad Zaki, Ahmed Aljanahi, Hamed AlGhadhban, E.A.E. Ali, V. Stashevsky","doi":"10.2118/207306-ms","DOIUrl":"https://doi.org/10.2118/207306-ms","url":null,"abstract":"\u0000 Objectives/Scope: The Magwa and Ostracod formations are tight and highly fractured carbonate reservoirs. At shallow depth (1600-1800 ft) and low stresses, wide, long and conductive propped fracture has proven to be the most effective stimulation technique for production enhancement. However, optimizing flow of the medium viscosity oil (17-27 API gravity) was a challenge both at initial phase (fracture fluid recovery and proppant flowback risks) and long-term (depletion, increasing water cut, emulsion tendency).\u0000 Methods, Procedures, Process: Historically, due to shallow depth, low reservoir pressure and low GOR, the optimum artificial lift method for the wells completed in the Magwa and Ostracod reservoirs was always sucker-rod pumps (SRP) with more than 300 wells completed to date. In 2019 a pilot re-development project was initiated to unlock reservoir potential and enhance productivity by introducing a massive high-volume propped fracturing stimulation that increased production rates by several folds. Consequently, initial production rates and drawdown had to be modelled to ensure proppant pack stability. Long-term artificial lift (AL) design was optimized using developed workflow based on reservoir modelling, available post-fracturing well testing data and production history match.\u0000 Results, Observations, Conclusions: Initial production results, in 16 vertical and slanted wells, were encouraging with an average 90 days production 4 to 8 times higher than of existing wells. However, the initial high gas volume and pressure is not favourable for SRP. In order to manage this, flexible AL approach was taken. Gas lift was preferred in the beginning and once the production falls below pre-defined PI and GOR, a conversion to SRP was done. Gas lift proved advantageous in handling solids such as residual proppant and in making sure that the well is free of solids before installing the pump. Continuous gas lift regime adjustments were taken to maximize drawdown. Periodical FBHP surveys were performed to calibrate the single well model for nodal analysis. However, there limitations were present in terms of maximizing the drawdown on one side and the high potential of forming GL induced emulsion on the other side. Horizontal wells with multi-stage fracturing are common field development method for such tight formations. However, in geological conditions of shallow and low temperature environment it represented a significant challenge to achieve fast and sufficient fracture fluid recovery by volume from multiple fractures without deteriorating the proppant pack stability. This paper outlines local solutions and a tailored workflow that were taken to optimize the production performance and give the brown field a second chance.\u0000 Novel/Additive Information: Overcoming the different production challenges through AL is one of the keys to unlock the reservoir potential for full field re-development. The Magwa and Ostracod formations are unique for stimulation","PeriodicalId":10981,"journal":{"name":"Day 4 Thu, November 18, 2021","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83040221","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":"Several Decades of Fluid Diversion Evolution, Is There a Good Solution?","authors":"A. Casero, A. Gomaa","doi":"10.2118/207953-ms","DOIUrl":"https://doi.org/10.2118/207953-ms","url":null,"abstract":"\u0000 The success of any matrix treatment depends upon the complete coverage of all zones. Consequently, the selection of the diversion technology is critical for treatment success. While various types of diverting agents are commercially available, the proper selection of optimal diverter depends on many factors, including well completion and history, compatibility with reservoir and treatment fluids, treatment objectives, operational constraints, and safety and environment considerations.\u0000 The study will cover five major types of non-mechanical diversion technologies considered as potential solutions for offshore deepwater oil reservoirs: dynamic diversion, relative permeability modifiers (RPM), viscoelastic surfactants (VES), particulate diversion, and perforation diversion. All of them, but a dynamic diversion, are based on different chemicals or products to be added to the injected treatment fluid, and occasionally some can be complementary to each other.\u0000 Given the offshore and deepwater settings, mechanical diversion techniques were not covered in the study, aiming to find a solution that would achieve acceptable diversion while minimizing operational effort, which would enable riser-less intervention and the use of light intervention techniques.\u0000 This study was driven by the need to effectively stimulate a 500ft of a cased and perforated interval with a permeability of 500 md, and injection rate limited to 16 bpm due to completion limitations. The sandstone formation, with static in situ temperature of 270F, was far beyond the applicability of dynamic diversion and, to achieve the desired full coverage for the planned scale inhibition treatment required and combination with another diverter system was needed.\u0000 The process applied included compatibility tests, regained permeability tests, and test well trials. Depending on the specific diversion product analyzed the testing procedures were adapted to obtain the information to properly guide to the optimal solution.","PeriodicalId":10981,"journal":{"name":"Day 4 Thu, November 18, 2021","volume":"9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89480304","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":"Accuracy and Precision of Reservoir Fluid Characterization Tests Through Blind Round-Robin Testing","authors":"A. Mawlod, Afzal Memon, J. Nighswander","doi":"10.2118/207749-ms","DOIUrl":"https://doi.org/10.2118/207749-ms","url":null,"abstract":"\u0000 Objectives/Scope: Oil and gas operators use a variety of reservoir engineering workflows in addition to the reservoir, production, and surface facility simulation tools to quantify reserves and complete field development planning activities. Reservoir fluid property data and models are fundamental input to all these workflows. Thus, it is important to understand the propagation of uncertainty in these various workflows arising from laboratory fluid property measured data and corresponding model uncertainty. The first step in understanding the impact of laboratory data uncertainty was to measure it, and as result, ADNOC Onshore undertook a detailed study to assess the performance of four selected reservoir fluid laboratories. The selected laboratories were evaluated using a blind round-robin study on stock tank liquid density and molar mass measurements, reservoir fluid flashed gas and flashed liquid C30+ reservoir composition gas chromatography measurements, and Constant Mass Expansion (CME) Pressure-Volume-Temperature (PVT) measurements using a variety of selected reservoir and pure components test fluids.\u0000 Upon completion of the analytical study and establishing a range of measurement uncertainty, a sensitivity analysis study was completed using an equation of state (EoS) model to study the impact of reservoir fluid composition and molecular weight measurement uncertainty on EoS model predictions.\u0000 Methods, Procedures, Process: A blind round test was designed and administered to assess the performance of the four laboratories. Strict confidentiality was maintained to conceal the identity of samples through blind test protocols. The round-robin tests were also witnessed by the researchers. The EoS sensitivity study was completed using the Peng Robinson EoS and a commercially available software package.\u0000 Results, Observations, Conclusions: The results of the fully blind reservoir fluid laboratory tests along with the statistical analysis of uncertainties will be presented in this paper. One of the laboratories had a systemic deviation in the measured plus fraction composition on black oil reference standard samples. The plus fraction concentration is typically the largest weight percent component in black oil systems and, along with the plus fraction molar mass, plays a crucial role in establishing the mole percent overall reservoir fluid compositions. Another laboratory had systemic issues related to chromatogram component integration errors that resulted in inconsistent carbon number concentration trends for various components. All laboratories failed to produce consistent molecular weight measurements for the reference samples. Finally, one laboratory had a relative deviation for P-V measurements that were significantly outside the acceptable range.\u0000 The EoS sensitivity study demonstrates that the fluid composition and stock tank oil molar mass measurements have a significant impact on EoS model predictions and hence the reservoir/production","PeriodicalId":10981,"journal":{"name":"Day 4 Thu, November 18, 2021","volume":"77 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83909278","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}