A. A. Terentiyev, Pavel Valeryevich Roschin, A. V. Nikitin, V. N. Kozhin, K. Pchela, I. I. Kireyev, Sergei Valerevich Demin, A. T. Litvin, I. Struchkov
One of the complications at the stage with steam injection start into the SAGD injection well in the Terrigenous reservoir with extra-heavy oil (EHO) is its injectivity rate. Traditionally, preheating the well bottom-hole (BH) zone with steam and subsequent recovery of hot water or steam through the annulus is used to get adequate injectivity. As an alternative to steam preheating it is proposed to inject an aromatic solvent/reagent to ensure sufficient well injectivity. Calculations were performed with the real reservoir model. The mutual influence of wells in SAGD blocks under the conditions of solvent/reagent injection was studied for this.
{"title":"Wait or Get the Oil: How SAGD Technology Implementation Options will Vary Future Production","authors":"A. A. Terentiyev, Pavel Valeryevich Roschin, A. V. Nikitin, V. N. Kozhin, K. Pchela, I. I. Kireyev, Sergei Valerevich Demin, A. T. Litvin, I. Struchkov","doi":"10.2118/201819-ms","DOIUrl":"https://doi.org/10.2118/201819-ms","url":null,"abstract":"\u0000 \u0000 \u0000 One of the complications at the stage with steam injection start into the SAGD injection well in the Terrigenous reservoir with extra-heavy oil (EHO) is its injectivity rate. Traditionally, preheating the well bottom-hole (BH) zone with steam and subsequent recovery of hot water or steam through the annulus is used to get adequate injectivity. As an alternative to steam preheating it is proposed to inject an aromatic solvent/reagent to ensure sufficient well injectivity. Calculations were performed with the real reservoir model. The mutual influence of wells in SAGD blocks under the conditions of solvent/reagent injection was studied for this.\u0000","PeriodicalId":359083,"journal":{"name":"Day 2 Tue, October 27, 2020","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130183186","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}
Syed M Amir, Mohammad Rasheed Khan, Ekarit Panacharoensawad, Serhii Kryvenko
Wrong manual interpretation from the log data about the formation type and other important information can be catastrophic for the company-operator. With Machine-Learning (ML) (a branch of Artificial Intelligence) algorithms, the interpretation of formation type from the log data has been addressed. As a result, we have successfully developed a program able to accurately predict the type of formation. Using the conventional Machine Learning technique of splitting the data into training, validation and test sets, we tried six different ML algorithms to fit with the training part of the data and then verify their prediction accuracy with cross-validation scores and cross-validation predictions which tests the performance of the classifiers (ML algorithms) on the validation set. The three best performing classifiers were selected and further improved by a search of classifier's best hyperparameters. These improved classifiers are further tested on unseen data to produce a comparative analysis. Our prediction accuracy with Receiver Operating Characteristic (ROC) scores and ROC-Area Under-the-Curve (ROC-AUC) for each type of formation from the log data lies in the range of 95-99%, except for formations such as shaly sandstone and shale (50% and 84% respectively). The reason for this seemed to be under-fitting i.e., during the training, the classifiers did not see enough instances of these types of formation to know exactly what characteristics of the data make the type of formation to be shaly sandstone or shale. The issue of under-fitting was verified by skimming through the data. To resolve this problem, we suggest training classifiers with a larger data with more targets (types of formation). Furthermore, during the data cleaning (prior to classifier training) and data analysis phases we have discovered important relationships between well logs and defined relative importance of each well log for different formations. This observation can be investigated further to help eliminate the use of multiple well logs while dealing with some formations (based on prior geological knowledge) and reduce the cost of the well logging operations. Using our program with a larger well log data consisting of more formation type instances, we can train the classifiers to accurately predict the formation type irrespectively of differences in formation type. Our program is dynamic in the sense that with different targets, i.e., type of formation fluid instead of type of formation or both together, it can successfully predict either or both targets. Increasing the numbers of data instances resulted in a better training and thus, more accurate predictions. Utilization of the program will make the formation-evaluation process easier, faster, automated and more-precise.
人工对测井数据中地层类型和其他重要信息的错误解释，对公司和运营商来说可能是灾难性的。利用机器学习(ML)(人工智能的一个分支)算法，可以从测井数据中解释地层类型。因此，我们成功开发了一个能够准确预测地层类型的程序。使用传统的机器学习技术将数据分成训练集、验证集和测试集，我们尝试了六种不同的ML算法来拟合数据的训练部分，然后用交叉验证分数和交叉验证预测来验证它们的预测准确性，这测试了分类器(ML算法)在验证集上的性能。选择三个表现最好的分类器，并通过搜索分类器的最佳超参数进一步改进。这些改进的分类器在未见过的数据上进一步测试，以产生比较分析。除了泥质砂岩和页岩等地层(分别为50%和84%)外，我们对每种地层的Receiver Operating Characteristic (ROC)分数和ROC- area Under-the-Curve (ROC- auc)的预测精度在95-99%之间。其原因似乎是拟合不足，即在训练过程中，分类器没有看到足够的这些类型的地层实例，无法确切地知道数据的哪些特征使地层类型为泥质砂岩或页岩。通过浏览数据验证了拟合不足的问题。为了解决这个问题，我们建议用更大的数据和更多的目标(编队类型)来训练分类器。此外，在数据清洗(分类器训练之前)和数据分析阶段，我们发现了测井曲线之间的重要关系，并定义了不同地层的每条测井曲线的相对重要性。这一观察结果可以进一步研究，以帮助在处理某些地层时(基于先前的地质知识)避免使用多口测井，并降低测井作业的成本。通过对包含更多地层类型实例的更大的测井数据进行训练，我们可以训练分类器准确地预测地层类型，而不考虑地层类型的差异。我们的程序是动态的，对于不同的目标，即不同的地层流体类型，而不是地层类型或两者一起，它可以成功地预测其中一个目标或两个目标。增加数据实例的数量可以得到更好的训练，从而得到更准确的预测。该程序的使用将使地层评估过程更容易、更快、自动化和更精确。
{"title":"Integration of Petrophysical Log Data with Computational Intelligence for the Development of a Lithology Predictor","authors":"Syed M Amir, Mohammad Rasheed Khan, Ekarit Panacharoensawad, Serhii Kryvenko","doi":"10.2118/202047-ms","DOIUrl":"https://doi.org/10.2118/202047-ms","url":null,"abstract":"\u0000 Wrong manual interpretation from the log data about the formation type and other important information can be catastrophic for the company-operator. With Machine-Learning (ML) (a branch of Artificial Intelligence) algorithms, the interpretation of formation type from the log data has been addressed. As a result, we have successfully developed a program able to accurately predict the type of formation.\u0000 Using the conventional Machine Learning technique of splitting the data into training, validation and test sets, we tried six different ML algorithms to fit with the training part of the data and then verify their prediction accuracy with cross-validation scores and cross-validation predictions which tests the performance of the classifiers (ML algorithms) on the validation set. The three best performing classifiers were selected and further improved by a search of classifier's best hyperparameters. These improved classifiers are further tested on unseen data to produce a comparative analysis.\u0000 Our prediction accuracy with Receiver Operating Characteristic (ROC) scores and ROC-Area Under-the-Curve (ROC-AUC) for each type of formation from the log data lies in the range of 95-99%, except for formations such as shaly sandstone and shale (50% and 84% respectively). The reason for this seemed to be under-fitting i.e., during the training, the classifiers did not see enough instances of these types of formation to know exactly what characteristics of the data make the type of formation to be shaly sandstone or shale. The issue of under-fitting was verified by skimming through the data. To resolve this problem, we suggest training classifiers with a larger data with more targets (types of formation). Furthermore, during the data cleaning (prior to classifier training) and data analysis phases we have discovered important relationships between well logs and defined relative importance of each well log for different formations. This observation can be investigated further to help eliminate the use of multiple well logs while dealing with some formations (based on prior geological knowledge) and reduce the cost of the well logging operations. Using our program with a larger well log data consisting of more formation type instances, we can train the classifiers to accurately predict the formation type irrespectively of differences in formation type.\u0000 Our program is dynamic in the sense that with different targets, i.e., type of formation fluid instead of type of formation or both together, it can successfully predict either or both targets. Increasing the numbers of data instances resulted in a better training and thus, more accurate predictions. Utilization of the program will make the formation-evaluation process easier, faster, automated and more-precise.","PeriodicalId":359083,"journal":{"name":"Day 2 Tue, October 27, 2020","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128563615","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}
Maxim Serggevich Zlobin, Sergey Vasilyevich Pilnyk, Y. S. Kolesnikov, Daniil Yurievich Kartinen, D. Krivolapov, P. Dobrokhleb, I. Masalida, A. Magda, Artem Andriyanovich Gerasimov, T. Soroka, I. Moiseenko, D. Andreev
The rapid development of the Achimov drilling program on the Yamal Peninsula requires an increasing of the drilling efficiency and complicating the wells construction. These factors create new challenges. The pursuit of increasing the productivity of the production wells leads to an increase in the length of horizontal reservoir sections and the number of hydraulic fracturing stages. Since the beginning of the complicated horizontal wells’ drilling at the Urengoyskoye oil and gas field, the average length of the horizontal wellbores has increased from 1000 to 1500 m, and the number of hydraulic fracturing – from 3 to 7 stages. Further extension of the horizontal well interval is associated with an increase in the bottomhole pressure and the risk of hydraulic fracturing. A pilot project for the horizontal wells’ construction in the Achimov deposits was launched at the Yamburgskoye field in 2019. Two such wells with the 1000 m horizontal interval were successfully drilled and completed. The results of the calculations and the obtained experience indicate a risk of the further horizontal interval increase. The implementation of managed pressure drilling (MPD) technology through the application of a low-density drilling mud and the precise control of the wellhead pressure can reduce the magnitude of repression during circulation and provide with an opportunity to drill longer intervals. Applying MPD technology makes it possible to provide safe drilling operations, tripping, early kick detection and fluid losses, running and cementing liners. The next step in the Yamburgskoye field pilot project was the construction of a well with a 6500 m depth and the 2500 m horizontal interval in the Achimov strata. Calculations results demonstrated that with the application of conventional drilling technologies there is a high probability of hydraulic fracturing if the horizontal section is more than 1500 meters. In addition, to make possible more fracturing stages execution, the use of Plug & Perf technology is required, which demands the liner cementing. The liner cementing, in turn, is most likely impossible with the traditional approach. It was decided to drill an extended productive strata interval with the MPD technology application. It was required to optimize each element of the drilling system, including BHA, drilling muds, and drilling regimes to achieve the best results. The necessary regulations and procedures have also been developed which purpose was not only to provide more safety during drilling operations, but also to reduce the time of well construction. MPD has become a new stage in the development of the Achimov program and made it possible to remove several geological restrictions. It also allowed to create conditions for the construction of more complex and efficient wells with a longer productive interval and many hydraulic fracturing stages. The experience obtained allows us to talk about the prospects of this solution for the construc
{"title":"Broaden Limits: Managed Pressure Drilling – A New Step for Achimov Horizontal Wells","authors":"Maxim Serggevich Zlobin, Sergey Vasilyevich Pilnyk, Y. S. Kolesnikov, Daniil Yurievich Kartinen, D. Krivolapov, P. Dobrokhleb, I. Masalida, A. Magda, Artem Andriyanovich Gerasimov, T. Soroka, I. Moiseenko, D. Andreev","doi":"10.2118/201866-ms","DOIUrl":"https://doi.org/10.2118/201866-ms","url":null,"abstract":"\u0000 The rapid development of the Achimov drilling program on the Yamal Peninsula requires an increasing of the drilling efficiency and complicating the wells construction. These factors create new challenges. The pursuit of increasing the productivity of the production wells leads to an increase in the length of horizontal reservoir sections and the number of hydraulic fracturing stages. Since the beginning of the complicated horizontal wells’ drilling at the Urengoyskoye oil and gas field, the average length of the horizontal wellbores has increased from 1000 to 1500 m, and the number of hydraulic fracturing – from 3 to 7 stages.\u0000 Further extension of the horizontal well interval is associated with an increase in the bottomhole pressure and the risk of hydraulic fracturing. A pilot project for the horizontal wells’ construction in the Achimov deposits was launched at the Yamburgskoye field in 2019. Two such wells with the 1000 m horizontal interval were successfully drilled and completed. The results of the calculations and the obtained experience indicate a risk of the further horizontal interval increase. The implementation of managed pressure drilling (MPD) technology through the application of a low-density drilling mud and the precise control of the wellhead pressure can reduce the magnitude of repression during circulation and provide with an opportunity to drill longer intervals.\u0000 Applying MPD technology makes it possible to provide safe drilling operations, tripping, early kick detection and fluid losses, running and cementing liners. The next step in the Yamburgskoye field pilot project was the construction of a well with a 6500 m depth and the 2500 m horizontal interval in the Achimov strata. Calculations results demonstrated that with the application of conventional drilling technologies there is a high probability of hydraulic fracturing if the horizontal section is more than 1500 meters. In addition, to make possible more fracturing stages execution, the use of Plug & Perf technology is required, which demands the liner cementing. The liner cementing, in turn, is most likely impossible with the traditional approach. It was decided to drill an extended productive strata interval with the MPD technology application. It was required to optimize each element of the drilling system, including BHA, drilling muds, and drilling regimes to achieve the best results. The necessary regulations and procedures have also been developed which purpose was not only to provide more safety during drilling operations, but also to reduce the time of well construction.\u0000 MPD has become a new stage in the development of the Achimov program and made it possible to remove several geological restrictions. It also allowed to create conditions for the construction of more complex and efficient wells with a longer productive interval and many hydraulic fracturing stages. The experience obtained allows us to talk about the prospects of this solution for the construc","PeriodicalId":359083,"journal":{"name":"Day 2 Tue, October 27, 2020","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128583025","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}
The "shale revolution" experience on the example of the Bazhenov formation (BF) development required a serious development program review and implementation. The modern approach to the Bazhenov formation development in the Russian Federation is approaching the final stage of the existing formation stimulation technologies improvement. The technical limit in completion is about to be reached. It becomes obvious that existing stimulation technologies do not allow creating more efficient "reservoir factories" in the Bazhenov formation. The paper's objective is an attempt to identify hypotheses and prerequisites, as well as possible prospects for the stimulation technologies development, to justify the use of new alternative systems for hydraulic fracturing (HF) with an assessment of their potential at the BF reservoirs.
{"title":"Potential and Possible Technological Solutions for Field Development of Unconventional Reservoirs: Bazhenov Formation","authors":"D. Bukharov, Y. Alekseev, A. Prodan, A. Nenko","doi":"10.2118/201818-ms","DOIUrl":"https://doi.org/10.2118/201818-ms","url":null,"abstract":"\u0000 The \"shale revolution\" experience on the example of the Bazhenov formation (BF) development required a serious development program review and implementation.\u0000 The modern approach to the Bazhenov formation development in the Russian Federation is approaching the final stage of the existing formation stimulation technologies improvement. The technical limit in completion is about to be reached. It becomes obvious that existing stimulation technologies do not allow creating more efficient \"reservoir factories\" in the Bazhenov formation. The paper's objective is an attempt to identify hypotheses and prerequisites, as well as possible prospects for the stimulation technologies development, to justify the use of new alternative systems for hydraulic fracturing (HF) with an assessment of their potential at the BF reservoirs.","PeriodicalId":359083,"journal":{"name":"Day 2 Tue, October 27, 2020","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115965544","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. Sabinin, T. Chichinina, V. Tulchinsky, M. Romero-Salcedo
Nowadays, Machine Learning (ML) is actively used in geophysical prospecting including seismic exploration. This study focuses on the applicability and feasibility of Deep Learning for the inverse problem in seismic exploration that is the estimation of the rock-physics parameters for a fractured reservoir, from seismic data. The main goal of this paper is to prove the efficiency of a neural network in estimating fractured medium parameters, represented as anisotropy parameters of HTI model. (HTI is "Horizontal Transverse Isotropy".) As such fracture parameters, we consider the normal and tangential weaknesses of fractures ΔN and ΔT, Thomsen anisotropy parameters ε, δ, γ, as well as the crack density e and the crack aspect ratio α (fracture opening). In addition, we consider a fractured medium, in which there are two fracture networks, characterized by two pairs of weaknesses (ΔN1, ΔT1) and (ΔN2, ΔT2); this is the so-called orthorhombic model. We validate the accuracy of our neural network by comparing the predicted parameter values with the a priori given. We use mathematic formulae, which relate the considered parameters estimation to different effective-medium anisotropy models of a fractured medium, such as Schoenberg's Linear Slip model, Hudson's model for penny-shaped cracks and Thomsen's model for aligned cracks in porous rock. In our study, seismic signatures (seismograms of the reflected waves PP and PS) of both the vertical UZ-component and the horizontal one UX are the inputs for the neural network. At the output, the network predicts fracture parameters and anisotropy parameters. The neural network is trained on synthetic seismograms of reflected waves, which were generated using 2D-elastic numerical finite-difference modelling. Thus we demonstrate the applicability of Deep Learning for estimation of the fractured medium parameters, by training the neural network on synthetic seismograms. The normal and tangential weaknesses of fractures ΔN and ΔT, the crack density and the crack aspect ratio (crack opening) are successfully estimated as well as the anisotropy parameters ε(V), δ(V) and γ(V). In the prediction of ΔN and ΔT, the relative error does not exceed 1.7% and 1.4%, respectively, and in the prediction of crack density e — from 0.9% to 1.4%. In predicting the anisotropy parameters ε(V), δ(V) and γ(V), the error does not exceed 1.6%, 1.7%, and 1.8%, respectively. However, in estimating the value of crack opening α, the result is an order of magnitude worse, an error of 14.2%. For the orthorhombic model, the prediction results are slightly worse than for the HTI model, but still within the acceptable accuracy. In predicting the fracture parameters for the first fracture network (ΔN1, ΔT1 and e1) the error does not exceed 2.3%, 4.2%, and 2.3%, respectively, and for the second fracture network (ΔN2, ΔT2 and e1) — respectively 4.3%, 5.7%, and 3.7%. This slight deterioration in the results (in comparison with HTI) is explained by
{"title":"Machine Learning for Fracture Parameter Estimation in Fractured Reservoirs from Seismic Data","authors":"G. Sabinin, T. Chichinina, V. Tulchinsky, M. Romero-Salcedo","doi":"10.2118/201934-ms","DOIUrl":"https://doi.org/10.2118/201934-ms","url":null,"abstract":"\u0000 Nowadays, Machine Learning (ML) is actively used in geophysical prospecting including seismic exploration. This study focuses on the applicability and feasibility of Deep Learning for the inverse problem in seismic exploration that is the estimation of the rock-physics parameters for a fractured reservoir, from seismic data. The main goal of this paper is to prove the efficiency of a neural network in estimating fractured medium parameters, represented as anisotropy parameters of HTI model. (HTI is \"Horizontal Transverse Isotropy\".) As such fracture parameters, we consider the normal and tangential weaknesses of fractures ΔN and ΔT, Thomsen anisotropy parameters ε, δ, γ, as well as the crack density e and the crack aspect ratio α (fracture opening). In addition, we consider a fractured medium, in which there are two fracture networks, characterized by two pairs of weaknesses (ΔN1, ΔT1) and (ΔN2, ΔT2); this is the so-called orthorhombic model.\u0000 We validate the accuracy of our neural network by comparing the predicted parameter values with the a priori given. We use mathematic formulae, which relate the considered parameters estimation to different effective-medium anisotropy models of a fractured medium, such as Schoenberg's Linear Slip model, Hudson's model for penny-shaped cracks and Thomsen's model for aligned cracks in porous rock.\u0000 In our study, seismic signatures (seismograms of the reflected waves PP and PS) of both the vertical UZ-component and the horizontal one UX are the inputs for the neural network. At the output, the network predicts fracture parameters and anisotropy parameters. The neural network is trained on synthetic seismograms of reflected waves, which were generated using 2D-elastic numerical finite-difference modelling.\u0000 Thus we demonstrate the applicability of Deep Learning for estimation of the fractured medium parameters, by training the neural network on synthetic seismograms. The normal and tangential weaknesses of fractures ΔN and ΔT, the crack density and the crack aspect ratio (crack opening) are successfully estimated as well as the anisotropy parameters ε(V), δ(V) and γ(V). In the prediction of ΔN and ΔT, the relative error does not exceed 1.7% and 1.4%, respectively, and in the prediction of crack density e — from 0.9% to 1.4%. In predicting the anisotropy parameters ε(V), δ(V) and γ(V), the error does not exceed 1.6%, 1.7%, and 1.8%, respectively. However, in estimating the value of crack opening α, the result is an order of magnitude worse, an error of 14.2%.\u0000 For the orthorhombic model, the prediction results are slightly worse than for the HTI model, but still within the acceptable accuracy. In predicting the fracture parameters for the first fracture network (ΔN1, ΔT1 and e1) the error does not exceed 2.3%, 4.2%, and 2.3%, respectively, and for the second fracture network (ΔN2, ΔT2 and e1) — respectively 4.3%, 5.7%, and 3.7%. This slight deterioration in the results (in comparison with HTI) is explained by ","PeriodicalId":359083,"journal":{"name":"Day 2 Tue, October 27, 2020","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129357757","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}
Tsimur Donalovich Hiliazitdzinau, Andrei Mikhailovich Valenkov, M. V. Kazak, S. Panin
In this paper, rheological properties of fracturing fluid samples on polymer and non-polymer basis are studied. The interdependence between effective viscosity, viscoelastic properties and the proppant carrying capacity of the studied composite systems is shown. The advantage of using the method of oscillatory rheometry in the amplitude sweep mode when predicting the sedimentation rate of proppant is observed. The possibility of using this method to study viscoelastic properties of fracturing fluids,both on the basis of classical and alternative gelling agents, was experimentally confirmed.
{"title":"Application of Oscillation Rheology Method to Studying Fracturing Fluids","authors":"Tsimur Donalovich Hiliazitdzinau, Andrei Mikhailovich Valenkov, M. V. Kazak, S. Panin","doi":"10.2118/202063-ms","DOIUrl":"https://doi.org/10.2118/202063-ms","url":null,"abstract":"\u0000 In this paper, rheological properties of fracturing fluid samples on polymer and non-polymer basis are studied. The interdependence between effective viscosity, viscoelastic properties and the proppant carrying capacity of the studied composite systems is shown. The advantage of using the method of oscillatory rheometry in the amplitude sweep mode when predicting the sedimentation rate of proppant is observed. The possibility of using this method to study viscoelastic properties of fracturing fluids,both on the basis of classical and alternative gelling agents, was experimentally confirmed.","PeriodicalId":359083,"journal":{"name":"Day 2 Tue, October 27, 2020","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114275416","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}
V. Nartymov, N. Pleshanov, R. Iskhakov, R. Nigmatullin, A. Ostankov, E. Sergeev
The era of production of readily available oil, which requires a relatively low level of capital costs, engineering solutions and the lack of use of new technological solutions, is over. At the moment, in the world and, specifically, in the perimeters of Gazpromneft, the bulk of the assets of hydrocarbon fields are complex in type and structure deposits with sufficiently high oil reserves, requiring both high capital costs and the adaptation of new technologies for effective development. Achimov formations Ach18-1 of the Yamburg deposit are bright representatives of the reservoir with a complex structure and very low, even for Achim formations, permeability. Average permeability of formation Ah 18-1 0.15 mD. At the moment, the only technology that allows achieving the profitability of the project is the use of wells with multi-stage hydraulic fracturing. However, a high share of hydrocarbon raw materials remains in the formation and for development, new technologies are being sought that will increase the level of net discounted income, as well as increase the oil recovery ratio. For consideration, the technology of mixing oil displacement with gas was chosen as one of the most promising technologies for the conditions of the Yamburg oil field. Gas injection technology was tested in a number of countries: the USA, Canada, Brazil, Venezuela and Norway, including was considered on some projects of Russia (USSR) (Figure 1). There are no direct analogues for Yamburg conditions, however, this technology allows us to obtain a REF increase of 1.5 to 2 times among the fields considered, on average, REF with the use of mixing displacement is about 46%, the increase relative to the standard Flooding is 7-12%. The promise of this method is that it can be used in deep-lying formations with low filtration-capacitive properties, high thermobaric conditions, the method allows not only to maintain formation pressure, but also to increase the oil recovery coefficient. Increase of oil recovery coefficient is achieved due to achievement of mixing pressure during gas injection, which leads to decrease of residual oil saturation and increase of phase permeability in gas-oil system. It is worth noting that the characteristics of the reservoir oil of the object under consideration (high gas content, a significant proportion of light fractions in the reservoir fluid composition) favor the use of gas methods to increase oil recovery, since the values of minimum mixing pressures for various types of injected gases (including pure methane and nitrogen) are lower than the initial reservoir pressure.Figure 1REF when applying mixing displacement technology. To assess the efficiency of mixing displacement at the Yamburg field, analytical calculations were carried out to determine the minimum mixing pressure with the formation oil of the Ach18-1 formation (the main development object). Based on the results of the calculations, the following conclusions were made:The mixin
{"title":"Practices of Miscible Displacement of Oil by Gas on the Achim Deposit of Yamburg Project","authors":"V. Nartymov, N. Pleshanov, R. Iskhakov, R. Nigmatullin, A. Ostankov, E. Sergeev","doi":"10.2118/201826-ms","DOIUrl":"https://doi.org/10.2118/201826-ms","url":null,"abstract":"\u0000 The era of production of readily available oil, which requires a relatively low level of capital costs, engineering solutions and the lack of use of new technological solutions, is over. At the moment, in the world and, specifically, in the perimeters of Gazpromneft, the bulk of the assets of hydrocarbon fields are complex in type and structure deposits with sufficiently high oil reserves, requiring both high capital costs and the adaptation of new technologies for effective development.\u0000 Achimov formations Ach18-1 of the Yamburg deposit are bright representatives of the reservoir with a complex structure and very low, even for Achim formations, permeability. Average permeability of formation Ah 18-1 0.15 mD.\u0000 At the moment, the only technology that allows achieving the profitability of the project is the use of wells with multi-stage hydraulic fracturing. However, a high share of hydrocarbon raw materials remains in the formation and for development, new technologies are being sought that will increase the level of net discounted income, as well as increase the oil recovery ratio.\u0000 For consideration, the technology of mixing oil displacement with gas was chosen as one of the most promising technologies for the conditions of the Yamburg oil field. Gas injection technology was tested in a number of countries: the USA, Canada, Brazil, Venezuela and Norway, including was considered on some projects of Russia (USSR) (Figure 1). There are no direct analogues for Yamburg conditions, however, this technology allows us to obtain a REF increase of 1.5 to 2 times among the fields considered, on average, REF with the use of mixing displacement is about 46%, the increase relative to the standard Flooding is 7-12%. The promise of this method is that it can be used in deep-lying formations with low filtration-capacitive properties, high thermobaric conditions, the method allows not only to maintain formation pressure, but also to increase the oil recovery coefficient. Increase of oil recovery coefficient is achieved due to achievement of mixing pressure during gas injection, which leads to decrease of residual oil saturation and increase of phase permeability in gas-oil system. It is worth noting that the characteristics of the reservoir oil of the object under consideration (high gas content, a significant proportion of light fractions in the reservoir fluid composition) favor the use of gas methods to increase oil recovery, since the values of minimum mixing pressures for various types of injected gases (including pure methane and nitrogen) are lower than the initial reservoir pressure.Figure 1REF when applying mixing displacement technology.\u0000 To assess the efficiency of mixing displacement at the Yamburg field, analytical calculations were carried out to determine the minimum mixing pressure with the formation oil of the Ach18-1 formation (the main development object). Based on the results of the calculations, the following conclusions were made:The mixin","PeriodicalId":359083,"journal":{"name":"Day 2 Tue, October 27, 2020","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131401657","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}
Vladimir Alekseevich Volkov, A. S. Shirokov, Dmitry Vyacheslavovich Grandov, Y. Utusikov
The paper presents an assessment of multilateral horizontal wells performance, which is relevant for the conditions of the Vankor Cluster of fields in view of the beginning of active development phase to involve low-productive reservoirs of Nizhnekhetskaya Formation into development. With the development of the asset reserves, a natural decrease in input productivity is observed in the zones with poorer properties. This circumstance requires the introduction of new promising technologies, such as multistage hydraulic fracturing in horizontal wells (Hz wells with MHF) and drilling multilateral horizontal wells (MHz) which have already proven themselves on the positive side under similar conditions in the fields of West and East Siberia.
{"title":"Experience in the Implementation and Research of Multilateral Horizontal Wells in the Vankor Cluster Field","authors":"Vladimir Alekseevich Volkov, A. S. Shirokov, Dmitry Vyacheslavovich Grandov, Y. Utusikov","doi":"10.2118/201901-ms","DOIUrl":"https://doi.org/10.2118/201901-ms","url":null,"abstract":"\u0000 The paper presents an assessment of multilateral horizontal wells performance, which is relevant for the conditions of the Vankor Cluster of fields in view of the beginning of active development phase to involve low-productive reservoirs of Nizhnekhetskaya Formation into development.\u0000 With the development of the asset reserves, a natural decrease in input productivity is observed in the zones with poorer properties. This circumstance requires the introduction of new promising technologies, such as multistage hydraulic fracturing in horizontal wells (Hz wells with MHF) and drilling multilateral horizontal wells (MHz) which have already proven themselves on the positive side under similar conditions in the fields of West and East Siberia.","PeriodicalId":359083,"journal":{"name":"Day 2 Tue, October 27, 2020","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131339447","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}
Pub Date : 2020-10-26DOI: 10.24887/0028-2448-2019-9-20-23
A. Gilmiyanova, Rf Ufa RN-BashNIPIneft Llc, G. A. Khamidullina, E. D. Suleimanov, A. A. Mironenko, M. V. Sukhova, Rf Tyumen Kharampurneftegas Llc
This paper presents the results of an integrated approach to the analysis of the geological structure and the subsequent of the productive Achimov deposits development: deposits X and Y located in Western Siberia. The main difficulties in the development of the Achimov deposits are associated with a high heterogeneity, a low degree of prediction of effective thicknesses, the difficulty of correctly calculating well flow rates, saturation behavior and, accordingly, water cut, and high production decline rates identified as a result of putting new wells into operation.
{"title":"Integrated Approach to the Analysis of Achimov Deposits for the Purpose of Optimizing Drilling","authors":"A. Gilmiyanova, Rf Ufa RN-BashNIPIneft Llc, G. A. Khamidullina, E. D. Suleimanov, A. A. Mironenko, M. V. Sukhova, Rf Tyumen Kharampurneftegas Llc","doi":"10.24887/0028-2448-2019-9-20-23","DOIUrl":"https://doi.org/10.24887/0028-2448-2019-9-20-23","url":null,"abstract":"\u0000 This paper presents the results of an integrated approach to the analysis of the geological structure and the subsequent of the productive Achimov deposits development: deposits X and Y located in Western Siberia. The main difficulties in the development of the Achimov deposits are associated with a high heterogeneity, a low degree of prediction of effective thicknesses, the difficulty of correctly calculating well flow rates, saturation behavior and, accordingly, water cut, and high production decline rates identified as a result of putting new wells into operation.","PeriodicalId":359083,"journal":{"name":"Day 2 Tue, October 27, 2020","volume":"457 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131825827","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}
A. Rebrikov, A. Koschenkov, Mikhail Anatolievich Soin, D. V. Vorobyev, S. Vasko, Denis Anatolievich Zakruzhni, A. Kravchenko
The history of drilling for oil in the Republic of Belarus began in the mid-1960s (Sosnok A. 2016), when the first industrial oil inflows were received in the Rechitsky district of the Gomel region, from wells No. 6 and No. 8. In the years that followed, local and international experience was leveraged to actively drill and develop the region’s oil deposits, using advanced technologies suited to the complex geological conditions of the Pripyat trough. The new century is calling for innovative approaches to solve well construction problems currently facing Belorusneft Production Association (PA). The need to improve drilling, completions, and production methods has led to the introduction of modern technology, with sweeping changes in all aspects of well construction. In 2019, exploration and production drilling in Belarus entered a new stage of development, in which reducing well construction time via the use of new, improved technologies became one of the highest priorities. A few decades ago, due to the complex geological structure that characterized Belarus deposits, drilling was carried out mainly by the rotary-turbine method. This method used roller cone and impregnated bits, which demonstrated quite good results; however, they did not compare to the performance of modern-day polycrystalline diamond compact (PDC) bits. In line with Belorusneft’s phased rig fleet refurbishment around 2016, PDC drill bits were introduced and deployed across all of the operator’s oilfields to handle "aggressive" hydraulic parameters in the Pripyat oil and gas basin. At the same time, there was a gradual transition from use of the turbine drilling and rotary bottom hole assembly (BHA) to BHAs that include a hydraulic positive displacement motor (PDM) and rotary steerable system (RSS). The volume of drilling with the newly configured BHA increased from 14 percent in 2016 to 83 percent by the end of 2019 Distribution of drilling volumes for Belorusneft, by year, by drive type. The increase of PDC bit usage was one of several factors that helped raise the run length per bit and the rate of penetration (ROP) to a new level. As shown in Table 2, due to the introduction of modern drilling technologies, the average ROP increased by more than 2 times since 2016, and amounted to 7.64 m/hr in 2019. With this higher ROP, it was possible to increase the total volume of drilling in 2019 by more than 1.5 times compared to 2016, without increasing the total number of drilling rigs. Average ROP and total drilling volumes for Belorusneft, by year. This paper describes the main challenges encountered in Belarus when drilling with Halliburton PDC bits, and the solutions delivered by the evolving bit design improvements. It includes the introduction of combined rock failure action bits with a higher penetration rate and, accordingly, associated cost savings. The paper also reveals the advantages of using these new bits when drilling wells in the complex geological conditions
白俄罗斯共和国的石油钻探历史始于20世纪60年代中期(Sosnok A. 2016)，当时在戈梅利地区的Rechitsky地区从6号井和8号井收到了第一批工业石油流入。在接下来的几年里，利用当地和国际经验，积极钻探和开发该地区的石油储量，使用适合普里皮亚季海槽复杂地质条件的先进技术。新世纪呼唤创新的方法来解决Belorusneft Production Association (PA)目前面临的建井问题。改进钻井、完井和生产方法的需求导致了现代技术的引入，使油井建设的各个方面发生了翻天覆地的变化。2019年，白俄罗斯的勘探和生产钻井进入了一个新的发展阶段，通过使用新的改进技术来缩短建井时间成为最优先考虑的事项之一。几十年前，由于白俄罗斯矿床的地质结构复杂，钻井主要采用旋转涡轮方法进行。该方法采用牙轮和浸渍钻头，取得了较好的效果;然而，它们的性能无法与现代聚晶金刚石紧凑型钻头(PDC)相比。根据Belorusneft在2016年前后对钻井平台进行的阶段性翻新，PDC钻头被引入并部署到所有运营商的油田，以处理Pripyat油气盆地的“激进”水力参数。与此同时，从使用涡轮钻井和旋转底部钻具组合(BHA)逐渐过渡到包括液压正排量马达(PDM)和旋转导向系统(RSS)的BHA。新配置的BHA的钻井量从2016年的14%增加到2019年底的83%，Belorusneft的钻井量按年、按驱动类型分布。PDC钻头使用率的增加是将钻头的下入长度和机械钻速(ROP)提高到一个新水平的几个因素之一。如表2所示，由于引入了现代钻井技术，自2016年以来，平均ROP增加了2倍以上，2019年达到7.64米/小时。有了更高的机械钻速，2019年的钻井总量可能比2016年增加1.5倍以上，而钻机总数却没有增加。Belorusneft的平均ROP和总钻井量，按年计算。本文介绍了在白俄罗斯使用哈里伯顿PDC钻头钻井时遇到的主要挑战，以及通过不断改进的钻头设计提供的解决方案。它包括引入具有更高穿透速度的组合岩石破坏作用钻头，从而节省相关成本。本文还揭示了在普里皮亚季凹陷盆地复杂地质条件下使用新型钻头钻井的优势。与常规设计的普通PDC钻头相比，白俄罗斯共和国是东半球第一个测试并确认创新钻头设计在不同剖面井的非均质岩石钻井中的高效率的国家之一。
{"title":"Using of the Drill Bit with Combined Action Significantly Reduce Well Construction Time in Belarus Republic","authors":"A. Rebrikov, A. Koschenkov, Mikhail Anatolievich Soin, D. V. Vorobyev, S. Vasko, Denis Anatolievich Zakruzhni, A. Kravchenko","doi":"10.2118/201850-ms","DOIUrl":"https://doi.org/10.2118/201850-ms","url":null,"abstract":"\u0000 The history of drilling for oil in the Republic of Belarus began in the mid-1960s (Sosnok A. 2016), when the first industrial oil inflows were received in the Rechitsky district of the Gomel region, from wells No. 6 and No. 8. In the years that followed, local and international experience was leveraged to actively drill and develop the region’s oil deposits, using advanced technologies suited to the complex geological conditions of the Pripyat trough. The new century is calling for innovative approaches to solve well construction problems currently facing Belorusneft Production Association (PA). The need to improve drilling, completions, and production methods has led to the introduction of modern technology, with sweeping changes in all aspects of well construction. In 2019, exploration and production drilling in Belarus entered a new stage of development, in which reducing well construction time via the use of new, improved technologies became one of the highest priorities.\u0000 A few decades ago, due to the complex geological structure that characterized Belarus deposits, drilling was carried out mainly by the rotary-turbine method. This method used roller cone and impregnated bits, which demonstrated quite good results; however, they did not compare to the performance of modern-day polycrystalline diamond compact (PDC) bits. In line with Belorusneft’s phased rig fleet refurbishment around 2016, PDC drill bits were introduced and deployed across all of the operator’s oilfields to handle \"aggressive\" hydraulic parameters in the Pripyat oil and gas basin. At the same time, there was a gradual transition from use of the turbine drilling and rotary bottom hole assembly (BHA) to BHAs that include a hydraulic positive displacement motor (PDM) and rotary steerable system (RSS). The volume of drilling with the newly configured BHA increased from 14 percent in 2016 to 83 percent by the end of 2019\u0000 Distribution of drilling volumes for Belorusneft, by year, by drive type.\u0000 The increase of PDC bit usage was one of several factors that helped raise the run length per bit and the rate of penetration (ROP) to a new level. As shown in Table 2, due to the introduction of modern drilling technologies, the average ROP increased by more than 2 times since 2016, and amounted to 7.64 m/hr in 2019. With this higher ROP, it was possible to increase the total volume of drilling in 2019 by more than 1.5 times compared to 2016, without increasing the total number of drilling rigs.\u0000 Average ROP and total drilling volumes for Belorusneft, by year.\u0000 This paper describes the main challenges encountered in Belarus when drilling with Halliburton PDC bits, and the solutions delivered by the evolving bit design improvements. It includes the introduction of combined rock failure action bits with a higher penetration rate and, accordingly, associated cost savings. The paper also reveals the advantages of using these new bits when drilling wells in the complex geological conditions","PeriodicalId":359083,"journal":{"name":"Day 2 Tue, October 27, 2020","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133933180","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}
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