An analytical solution is presented for pressure- and rate-transient behavior of an array of n parallel and fractured horizontal wells in an unconventional reservoir. Wells are of equal length but otherwise of unidentical properties. Each well has an arbitrary number of uniformly spaced identical, finite-conductivity fractures and is surrounded by a stimulated reservoir volume (SRV). The properties of hydraulic fractures (HFs) and SRVs may vary from well to well. Different properties may also be assigned to the unstimulated reservoir sections between wells. Natural fractures in stimulated and unstimulated reservoir volumes are accounted for by transient dual-porosity idealization. The flow domain is divided into blocks of 1D flow under the trilinear-flow assumption. Solution for each block is obtained analytically and coupled with the solutions for the neighboring blocks by the continuity of pressure and flux at the block interfaces. Drainage volumes of wells are adjusted based on the variation of well production rates because of moving no-flow boundaries between wells. The superposition principle is applied to consider variable-production conditions as well as nonsynchronous production and shut-in schedules of wells. The final solution is in the form of a matrix-vector equation in the Laplace transform domain and inverted into the time domain numerically. The model is robust and reasonably accurate for most practical applications of single-phase oil and gas production from multiple wells in an unconventional reservoir. It is an efficient tool to assess well interference effects for different well completion designs and varying reservoir characteristics. The speed of the model makes it useful for pressure-transient and production-data analysis, as well as for the initial calibration and verification of more complex numerical models.
本文提出了非常规储层中 n 个平行压裂水平井阵列的压力和速率瞬态行为的分析解决方案。井的长度相等，但其他属性并不相同。每口井都有任意数量的间距一致的有限传导性裂缝，并被激发储层容积（SRV）包围。不同油井的水力压裂（HF）和油藏体积（SRV）的属性可能不同。井与井之间未受刺激储层段的属性也可能不同。受刺激和未受刺激储层体积中的天然裂缝通过瞬态双孔隙理想化加以考虑。在三线流假设下，流动域被划分为一维流动区块。每个区块的解都是通过分析得到的，并通过区块界面上压力和流量的连续性与相邻区块的解耦合。由于井间无流边界的移动，根据油井生产率的变化调整油井的排水量。叠加原理用于考虑可变生产条件以及油井的非同步生产和关井计划。最终解法是拉普拉斯变换域中的矩阵向量方程形式，并以数值方式反演到时域。对于非常规储层中多口油井的单相油气生产的大多数实际应用，该模型都非常稳健和准确。它是评估不同完井设计和不同储层特征下油井干扰效应的有效工具。该模型速度快，可用于压力瞬态和生产数据分析，以及更复杂数值模型的初步校准和验证。
{"title":"Pressure- and Rate-Transient Model for an Array of Interfering Fractured Horizontal Wells in Unconventional Reservoirs","authors":"E. Ozkan, M. Makhatova","doi":"10.2118/215031-pa","DOIUrl":"https://doi.org/10.2118/215031-pa","url":null,"abstract":"\u0000 An analytical solution is presented for pressure- and rate-transient behavior of an array of n parallel and fractured horizontal wells in an unconventional reservoir. Wells are of equal length but otherwise of unidentical properties. Each well has an arbitrary number of uniformly spaced identical, finite-conductivity fractures and is surrounded by a stimulated reservoir volume (SRV). The properties of hydraulic fractures (HFs) and SRVs may vary from well to well. Different properties may also be assigned to the unstimulated reservoir sections between wells. Natural fractures in stimulated and unstimulated reservoir volumes are accounted for by transient dual-porosity idealization. The flow domain is divided into blocks of 1D flow under the trilinear-flow assumption. Solution for each block is obtained analytically and coupled with the solutions for the neighboring blocks by the continuity of pressure and flux at the block interfaces. Drainage volumes of wells are adjusted based on the variation of well production rates because of moving no-flow boundaries between wells. The superposition principle is applied to consider variable-production conditions as well as nonsynchronous production and shut-in schedules of wells. The final solution is in the form of a matrix-vector equation in the Laplace transform domain and inverted into the time domain numerically. The model is robust and reasonably accurate for most practical applications of single-phase oil and gas production from multiple wells in an unconventional reservoir. It is an efficient tool to assess well interference effects for different well completion designs and varying reservoir characteristics. The speed of the model makes it useful for pressure-transient and production-data analysis, as well as for the initial calibration and verification of more complex numerical models.","PeriodicalId":22252,"journal":{"name":"SPE Journal","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141136275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yumin Li, Xiaoping Li, Yonggang Duan, M. Wei, Ke Meng
The low porosity and low permeability of shale gas reservoirs make fracturing technology an indispensable part of shale gas reservoir development. The initial stage of shale gas development is characterized by shallow direct wells, but with the advancement of drilling and completion technology in the development of unconventional oil and gas reservoirs, horizontal wells and fracturing technology have gradually become the key methods for the effective development of oil and gas reservoirs. “Geology-engineering integration” has gradually become a hot spot in the research of horizontal well fracturing. The factors affecting the development of shale gas reservoirs are subdivided into “geological sweet spot” and “engineering sweet spot” influencing factors. Geological sweet spot refers to the area where the reservoir is rich in hydrocarbons or organic matter; engineering sweet spot refers to the area with good fracturability in the later fracturing and reforming of the reservoir. The shale gas sweet spot area should have the characteristics of high gas content, high fracturable, and high efficiency. Comprehensively evaluating the physical properties and brittleness characteristics can provide certain guidance for shale gas horizontal well segmentation.
{"title":"Segmentation Study of Deep Shale Gas Horizontal Wells of the South Sichuan Shale Gas","authors":"Yumin Li, Xiaoping Li, Yonggang Duan, M. Wei, Ke Meng","doi":"10.2118/221451-pa","DOIUrl":"https://doi.org/10.2118/221451-pa","url":null,"abstract":"\u0000 The low porosity and low permeability of shale gas reservoirs make fracturing technology an indispensable part of shale gas reservoir development. The initial stage of shale gas development is characterized by shallow direct wells, but with the advancement of drilling and completion technology in the development of unconventional oil and gas reservoirs, horizontal wells and fracturing technology have gradually become the key methods for the effective development of oil and gas reservoirs. “Geology-engineering integration” has gradually become a hot spot in the research of horizontal well fracturing. The factors affecting the development of shale gas reservoirs are subdivided into “geological sweet spot” and “engineering sweet spot” influencing factors. Geological sweet spot refers to the area where the reservoir is rich in hydrocarbons or organic matter; engineering sweet spot refers to the area with good fracturability in the later fracturing and reforming of the reservoir. The shale gas sweet spot area should have the characteristics of high gas content, high fracturable, and high efficiency. Comprehensively evaluating the physical properties and brittleness characteristics can provide certain guidance for shale gas horizontal well segmentation.","PeriodicalId":22252,"journal":{"name":"SPE Journal","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141142284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lei Jiang, Li Chen, Hua Yu, Morten Kristensen, A. Gisolf, H. Dumont
A new definition of the radius of investigation (ROI) is proposed to overcome the ambiguity present in the results from conventional ROI quantification methods. The term ROI is commonly used to quantify the minimum reservoir size or the distance to a potential boundary evaluated through pressure transient testing. However, the various methods available in the literature to quantify ROI often provide different answers stemming from varying assumptions and thus often lead to confusion in terms of the appropriate definition to choose. Although the ROI method developed by Van Poolen is well recognized in the industry, there is still debate about its general applicability because it is limited to a constant-rate flow period and is insensitive to flow rate, flow sequence, gauge resolution, and measurement noise level. This contrasts with operational experience, where a higher flow rate, higher gauge precision, and lower level of measurement noise lead to higher quality pressure transient testing data from which reservoir boundaries, or other features, can be identified farther away from the wellbore. In other words, higher flow rates, better gauges, and lower noise levels can lead to a larger achievable ROI. We propose a new definition of ROI, which is the detectable ROI for each drawdown or buildup flow period. The detectable ROI is derived from the actual pressure derivative response and not from a generic model assumption. By defining a derivative noise envelope, the new method clearly identifies the time when the derivative deviates from an unbounded model due to the presence of a boundary and thus provides an estimate of the detectable ROI for the analyzed period. This method overcomes the limitations of most conventional methods and provides ROI predictions that depend on flow rate and gauge noise while maintaining a consistent result with the current pressure transient interpretation. While detectable ROI is applicable for general drawdown/buildup pressure transient tests, the concept was developed with deep transient testing (DTT) in mind.
提出了勘探半径（ROI）的新定义，以克服传统 ROI 量化方法结果中存在的模糊性。术语 ROI 通常用于量化最小储层尺寸或通过压力瞬态测试评估的潜在边界的距离。然而，文献中用于量化投资回报率的各种方法往往因假设条件的不同而给出不同的答案，因此常常导致在选择适当定义方面的混乱。尽管 Van Poolen 开发的投资回报率方法在业内广受认可，但由于该方法仅限于恒定流速时段，且对流速、流动顺序、压力表分辨率和测量噪音水平不敏感，因此其普遍适用性仍存在争议。这与实际操作经验形成了鲜明对比，在实际操作中，较高的流速、较高的压力表精度和较低的测量噪音水平会带来更高质量的压力瞬态测试数据，从而可以在距离井筒较远的地方识别储层边界或其他特征。换句话说，更高的流速、更好的压力表和更低的噪音水平可以带来更大的可实现投资回报率。我们提出了一个新的 ROI 定义，即每个缩减或增大流量期间的可探测 ROI。可探测 ROI 来自实际压力导数响应，而非通用模型假设。通过定义导数噪声包络线，新方法可以清楚地识别出导数因边界的存在而偏离无边界模型的时间，从而为分析时段提供可探测 ROI 的估计值。这种方法克服了大多数传统方法的局限性，可提供取决于流速和压力表噪声的 ROI 预测，同时与当前的压力瞬态解释结果保持一致。虽然可探测 ROI 适用于一般的缩减/增大压力瞬态测试，但这一概念是针对深层瞬态测试 (DTT) 而开发的。
{"title":"Detectable Radius of Investigation for One Flow Period with Bourdet Derivative","authors":"Lei Jiang, Li Chen, Hua Yu, Morten Kristensen, A. Gisolf, H. Dumont","doi":"10.2118/210150-pa","DOIUrl":"https://doi.org/10.2118/210150-pa","url":null,"abstract":"\u0000 A new definition of the radius of investigation (ROI) is proposed to overcome the ambiguity present in the results from conventional ROI quantification methods. The term ROI is commonly used to quantify the minimum reservoir size or the distance to a potential boundary evaluated through pressure transient testing. However, the various methods available in the literature to quantify ROI often provide different answers stemming from varying assumptions and thus often lead to confusion in terms of the appropriate definition to choose. Although the ROI method developed by Van Poolen is well recognized in the industry, there is still debate about its general applicability because it is limited to a constant-rate flow period and is insensitive to flow rate, flow sequence, gauge resolution, and measurement noise level. This contrasts with operational experience, where a higher flow rate, higher gauge precision, and lower level of measurement noise lead to higher quality pressure transient testing data from which reservoir boundaries, or other features, can be identified farther away from the wellbore. In other words, higher flow rates, better gauges, and lower noise levels can lead to a larger achievable ROI.\u0000 We propose a new definition of ROI, which is the detectable ROI for each drawdown or buildup flow period. The detectable ROI is derived from the actual pressure derivative response and not from a generic model assumption. By defining a derivative noise envelope, the new method clearly identifies the time when the derivative deviates from an unbounded model due to the presence of a boundary and thus provides an estimate of the detectable ROI for the analyzed period.\u0000 This method overcomes the limitations of most conventional methods and provides ROI predictions that depend on flow rate and gauge noise while maintaining a consistent result with the current pressure transient interpretation. While detectable ROI is applicable for general drawdown/buildup pressure transient tests, the concept was developed with deep transient testing (DTT) in mind.","PeriodicalId":22252,"journal":{"name":"SPE Journal","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141140914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The objective of this study is to develop a systematic and novel workflow for the automated and objective characterization of carbonate reservoirs with the help of deep learning architectures. An image database of more than 6,000 carbonate thin-section images was generated using the optical microscope and image augmentation techniques. Five features, namely clay/silt/mineral, calcite, pores, fossils, and opaque minerals, were identified with the help of manual petrography of the thin sections under the microscope. A total of four deep learning models were developed, which included U-Net, U-Net with ResNet34 backbone, U-Net with Mobilenetv2 backbone, and LinkNet with ResNet34 backbone. The Ensemble model of U-Net + ResNet34 and U-Net + MobileNetv2 yielded the highest intersection over union (IoU) score of 75%, followed by the U-Net + ResNet34 model with an IoU score of 61%. The models struggled with class imbalance, which was very prominent in the image database, with classes such as fossils and opaques considered to be rare. The statistical analysis of the relative errors revealed that the major classes play a more important role in increasing the final IoU score as opposed to the common understanding that the rare classes affect the model performance. The novel workflow developed in this paper can be extended to real carbonate reservoirs for time efficient, objective, and accurate characterization.
{"title":"Automated Reservoir Characterization of Carbonate Rocks using Deep Learning Image Segmentation Approach","authors":"S. Nande, S. Patwardhan","doi":"10.2118/219769-pa","DOIUrl":"https://doi.org/10.2118/219769-pa","url":null,"abstract":"\u0000 The objective of this study is to develop a systematic and novel workflow for the automated and objective characterization of carbonate reservoirs with the help of deep learning architectures. An image database of more than 6,000 carbonate thin-section images was generated using the optical microscope and image augmentation techniques. Five features, namely clay/silt/mineral, calcite, pores, fossils, and opaque minerals, were identified with the help of manual petrography of the thin sections under the microscope. A total of four deep learning models were developed, which included U-Net, U-Net with ResNet34 backbone, U-Net with Mobilenetv2 backbone, and LinkNet with ResNet34 backbone. The Ensemble model of U-Net + ResNet34 and U-Net + MobileNetv2 yielded the highest intersection over union (IoU) score of 75%, followed by the U-Net + ResNet34 model with an IoU score of 61%. The models struggled with class imbalance, which was very prominent in the image database, with classes such as fossils and opaques considered to be rare. The statistical analysis of the relative errors revealed that the major classes play a more important role in increasing the final IoU score as opposed to the common understanding that the rare classes affect the model performance. The novel workflow developed in this paper can be extended to real carbonate reservoirs for time efficient, objective, and accurate characterization.","PeriodicalId":22252,"journal":{"name":"SPE Journal","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141056323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lei Li, Mingjian Wang, Yu-liang Su, Xiao-gang Gao, Wen-dong Wang, Jia-wei Tu, Xin-hao Wang
Asphaltenes are heavy aromatic hydrocarbon compounds contained in reservoir fluids and may precipitate when the reservoir pressure is reduced by production or when gas is injected into the reservoir, and then further deposit on pore-throat surfaces causing reservoir damage. At present, the research on asphaltene precipitation and reservoir damage is carried out in conventional reservoirs, and the influence of CO2 injection under high-pressure, high-temperature (HPHT) conditions has not yet been clearly understood. In this work, we combined perturbed-chain statistical association fluid theory (PC-SAFT) calculation, experiments, phase-state simulation, and numerical simulation to predict the asphaltene precipitation with different pressures, temperatures, and amounts of injected gas and to clarify the influence on reservoir permeability and oil production when using CO2 injection. The results show that the precipitation of asphaltenes in the process of CO2 injection is the desorption of colloid-asphaltene inclusions caused by gas molecules and then the mutual polymerization process between dispersed asphaltene molecules. CO2 injection will increase the amount of precipitation and move the precipitation curve to the right side. The degree of permeability reduction caused by the deposition of asphaltenes in the core is 12.87–37.54%; the deposition of asphaltenes in the reservoir is mainly around the injection/production wells and along the injected gas profile. Considering asphaltenes, the oil recovery degree is reduced by 1.5%, and the injection rate is reduced by 17%. The reservoir pressure, temperature, and physical properties have a strong correlation with the degree of reservoir damage, while the initial asphaltene content has a low correlation. This work will be of great interest to operators seeking to enhance oil recovery by CO2 injection in deep reservoirs.
{"title":"Investigation of Asphaltene Precipitation and Reservoir Damage during CO2 Flooding in High-Pressure, High-Temperature Sandstone Oil Reservoirs","authors":"Lei Li, Mingjian Wang, Yu-liang Su, Xiao-gang Gao, Wen-dong Wang, Jia-wei Tu, Xin-hao Wang","doi":"10.2118/214805-pa","DOIUrl":"https://doi.org/10.2118/214805-pa","url":null,"abstract":"\u0000 Asphaltenes are heavy aromatic hydrocarbon compounds contained in reservoir fluids and may precipitate when the reservoir pressure is reduced by production or when gas is injected into the reservoir, and then further deposit on pore-throat surfaces causing reservoir damage. At present, the research on asphaltene precipitation and reservoir damage is carried out in conventional reservoirs, and the influence of CO2 injection under high-pressure, high-temperature (HPHT) conditions has not yet been clearly understood. In this work, we combined perturbed-chain statistical association fluid theory (PC-SAFT) calculation, experiments, phase-state simulation, and numerical simulation to predict the asphaltene precipitation with different pressures, temperatures, and amounts of injected gas and to clarify the influence on reservoir permeability and oil production when using CO2 injection. The results show that the precipitation of asphaltenes in the process of CO2 injection is the desorption of colloid-asphaltene inclusions caused by gas molecules and then the mutual polymerization process between dispersed asphaltene molecules. CO2 injection will increase the amount of precipitation and move the precipitation curve to the right side. The degree of permeability reduction caused by the deposition of asphaltenes in the core is 12.87–37.54%; the deposition of asphaltenes in the reservoir is mainly around the injection/production wells and along the injected gas profile. Considering asphaltenes, the oil recovery degree is reduced by 1.5%, and the injection rate is reduced by 17%. The reservoir pressure, temperature, and physical properties have a strong correlation with the degree of reservoir damage, while the initial asphaltene content has a low correlation. This work will be of great interest to operators seeking to enhance oil recovery by CO2 injection in deep reservoirs.","PeriodicalId":22252,"journal":{"name":"SPE Journal","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141132287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
CO2 storage in saline aquifers may contribute to a 90% share in preventing emissions to the atmosphere. Due to low CO2 viscosity at the subsurface often found in supercritical (sc) conditions, the injected CO2 may spread quickly at the formation top and increase the probability of leakage. This work relates to improved CO2 storage in saline aquifers by effective viscosification of the sc-CO2 at very low concentrations of engineered oligomers and the effectiveness of slug injection of viscosified CO2 (vis-CO2). We present the results from X-ray computed tomography (CT) imaging to advance the understanding of two-phase CO2-brine flow in porous media and firmly establish the transport mechanisms. X-ray CT imaging of displacement experiments is conducted to quantify the in-situ sc-CO2 saturation spatiotemporally. In neat CO2 injection, gravity override and adverse mobility ratio may result in early breakthrough and low sweep efficiency. We find cumulative brine production from the fraction collector to be lower than X-ray CT imaging at 2 pore volume (PV) injection. The difference between the two is attributed to the solubility of the produced water in the produced CO2 at atmospheric pressure. We show that when the solubility is accounted for, there is a good agreement between direct measurements and in-situ saturation results. There are three reports (two by the same group) that oligomers of 1-decene (O1D) with six repeat units may have marginal CO2 viscosification. The majority of published work by other groups shows that O1D with six repeat units and higher are effective CO2 viscosifiers. In the past, we have demonstrated the effectiveness of an O1D in the displacement of brine by CO2 at a concentration of 1.5 wt%. The effectiveness is examined and identified by three different methods. In this work, we show that the same oligomer is effective at a low concentration of 0.6 wt%. The oligomer slows the breakthrough by 1.6 times and improves the brine production by 34% in the horizontal orientation. X-ray CT imaging results reveal that such a large effect may be from the increase in the interfacial elasticity. We also show that there is no need for continuous injection of the oligomer. A slug of 0.3 PV injection (PVI) of vis-CO2 followed by neat CO2 injection has the same effectiveness as the continuous injection of the vis-CO2. In this work, we also demonstrate the effectiveness of a new engineered molecule at 0.3 wt% that may increase residual trapping by about 35%. The combination of mobility control and residual brine saturation reduction is expected to improve CO2 storage by effective viscosification with low concentrations of oligomers.
{"title":"Spatiotemporal X-Ray Imaging of Neat and Viscosified CO2 in Displacement of Brine-Saturated Porous Media","authors":"Boxin Ding, A. Kantzas, A. Firoozabadi","doi":"10.2118/214842-pa","DOIUrl":"https://doi.org/10.2118/214842-pa","url":null,"abstract":"\u0000 CO2 storage in saline aquifers may contribute to a 90% share in preventing emissions to the atmosphere. Due to low CO2 viscosity at the subsurface often found in supercritical (sc) conditions, the injected CO2 may spread quickly at the formation top and increase the probability of leakage. This work relates to improved CO2 storage in saline aquifers by effective viscosification of the sc-CO2 at very low concentrations of engineered oligomers and the effectiveness of slug injection of viscosified CO2 (vis-CO2). We present the results from X-ray computed tomography (CT) imaging to advance the understanding of two-phase CO2-brine flow in porous media and firmly establish the transport mechanisms.\u0000 X-ray CT imaging of displacement experiments is conducted to quantify the in-situ sc-CO2 saturation spatiotemporally. In neat CO2 injection, gravity override and adverse mobility ratio may result in early breakthrough and low sweep efficiency. We find cumulative brine production from the fraction collector to be lower than X-ray CT imaging at 2 pore volume (PV) injection. The difference between the two is attributed to the solubility of the produced water in the produced CO2 at atmospheric pressure. We show that when the solubility is accounted for, there is a good agreement between direct measurements and in-situ saturation results.\u0000 There are three reports (two by the same group) that oligomers of 1-decene (O1D) with six repeat units may have marginal CO2 viscosification. The majority of published work by other groups shows that O1D with six repeat units and higher are effective CO2 viscosifiers. In the past, we have demonstrated the effectiveness of an O1D in the displacement of brine by CO2 at a concentration of 1.5 wt%. The effectiveness is examined and identified by three different methods. In this work, we show that the same oligomer is effective at a low concentration of 0.6 wt%. The oligomer slows the breakthrough by 1.6 times and improves the brine production by 34% in the horizontal orientation. X-ray CT imaging results reveal that such a large effect may be from the increase in the interfacial elasticity. We also show that there is no need for continuous injection of the oligomer. A slug of 0.3 PV injection (PVI) of vis-CO2 followed by neat CO2 injection has the same effectiveness as the continuous injection of the vis-CO2. In this work, we also demonstrate the effectiveness of a new engineered molecule at 0.3 wt% that may increase residual trapping by about 35%. The combination of mobility control and residual brine saturation reduction is expected to improve CO2 storage by effective viscosification with low concentrations of oligomers.","PeriodicalId":22252,"journal":{"name":"SPE Journal","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141029687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Intensive growth of geological carbon sequestration has motivated the energy sector to diversify its storage portfolios, given the background of climate change mitigation. As an abundant unconventional reserve, shale gas reservoirs play a critical role in providing sufficient energy supply and geological carbon storage potentials. However, the low recovery factors of the primary recovery stage are a major concern during reservoir operations. Although injecting CO2 can resolve the dual challenges of improving the recovery factors and storing CO2 permanently, forecasting the reservoir performance heavily relies on reservoir simulation, which is a time-consuming process. In recent years, pioneered studies demonstrated that using machine learning (ML) algorithms can make predictions in an accurate and timely manner but fails to capture the time-series and spatial features of operational realities. In this work, we carried out a novel combinational framework including the artificial neural network (ANN, i.e., multilayer perceptron or MLP) and long short-term memory (LSTM) or bi-directional LSTM (Bi-LSTM) algorithms, tackling the challenges mentioned before. In addition, the deployment of ML algorithms in the petroleum industry is insufficient because of the field data shortage. Here, we also demonstrated an approach for synthesizing field-specific data sets using a numerical method. The findings of this work can be articulated from three perspectives. First, the cumulative gas recovery factor can be improved by 6% according to the base reservoir model with input features of the Barnett shale, whereas the CO2 retention factor sharply declined to 40% after the CO2 breakthrough. Second, using combined ANN and LSTM (ANN-LSTM)/Bi-LSTM is a feasible alternative to reservoir simulation that can be around 120 times faster than the numerical approach. By comparing an evaluation matrix of algorithms, we observed that trade-offs exist between computational time and accuracy in selecting different algorithms. This work provides fundamental support to the shale gas industry in developing comparable ML-based tools to replace traditional numerical simulation in a timely manner.
在减缓气候变化的背景下，地质碳封存技术的迅猛发展促使能源部门将其封存组合多样化。页岩气藏作为一种丰富的非常规储量，在提供充足的能源供应和地质碳封存潜力方面发挥着至关重要的作用。然而，初级采收阶段的低采收率是储层运营过程中的一个主要问题。虽然注入二氧化碳可以解决提高采收率和永久封存二氧化碳的双重难题，但储层性能预测严重依赖于储层模拟，而储层模拟是一个耗时的过程。近年来，先驱研究表明，使用机器学习（ML）算法可以准确及时地进行预测，但却无法捕捉实际操作的时间序列和空间特征。在这项工作中，我们采用了一种新颖的组合框架，包括人工神经网络（ANN，即多层感知器或 MLP）和长短期记忆（LSTM）或双向 LSTM（Bi-LSTM）算法，以应对上述挑战。此外，由于油田数据短缺，ML 算法在石油行业的应用还不够充分。在此，我们还展示了一种使用数值方法合成特定油田数据集的方法。这项工作的发现可以从三个方面来阐述。首先，根据输入巴尼特页岩特征的基础储层模型，累积采气系数可提高 6%，而二氧化碳突破后，二氧化碳保留系数急剧下降至 40%。其次，使用组合 ANN 和 LSTM（ANN-LSTM）/Bi-LSTM 是一种可行的储层模拟替代方法，其速度是数值方法的 120 倍左右。通过比较算法评估矩阵，我们发现在选择不同算法时，计算时间和精度之间存在权衡。这项工作为页岩气行业开发基于 ML 的可比工具以及时取代传统数值模拟提供了基础支持。
{"title":"A Combined Neural Network Forecasting Approach for CO2-Enhanced Shale Gas Recovery","authors":"Zhenqian Xue, Yuming Zhang, Haoming Ma, Yang Lu, Kai Zhang, Yizheng Wei, Sheng Yang, Muming Wang, Maojie Chai, Zhe Sun, Peng Deng, Zhangxin Chen","doi":"10.2118/219774-pa","DOIUrl":"https://doi.org/10.2118/219774-pa","url":null,"abstract":"\u0000 Intensive growth of geological carbon sequestration has motivated the energy sector to diversify its storage portfolios, given the background of climate change mitigation. As an abundant unconventional reserve, shale gas reservoirs play a critical role in providing sufficient energy supply and geological carbon storage potentials. However, the low recovery factors of the primary recovery stage are a major concern during reservoir operations. Although injecting CO2 can resolve the dual challenges of improving the recovery factors and storing CO2 permanently, forecasting the reservoir performance heavily relies on reservoir simulation, which is a time-consuming process. In recent years, pioneered studies demonstrated that using machine learning (ML) algorithms can make predictions in an accurate and timely manner but fails to capture the time-series and spatial features of operational realities. In this work, we carried out a novel combinational framework including the artificial neural network (ANN, i.e., multilayer perceptron or MLP) and long short-term memory (LSTM) or bi-directional LSTM (Bi-LSTM) algorithms, tackling the challenges mentioned before. In addition, the deployment of ML algorithms in the petroleum industry is insufficient because of the field data shortage. Here, we also demonstrated an approach for synthesizing field-specific data sets using a numerical method. The findings of this work can be articulated from three perspectives. First, the cumulative gas recovery factor can be improved by 6% according to the base reservoir model with input features of the Barnett shale, whereas the CO2 retention factor sharply declined to 40% after the CO2 breakthrough. Second, using combined ANN and LSTM (ANN-LSTM)/Bi-LSTM is a feasible alternative to reservoir simulation that can be around 120 times faster than the numerical approach. By comparing an evaluation matrix of algorithms, we observed that trade-offs exist between computational time and accuracy in selecting different algorithms. This work provides fundamental support to the shale gas industry in developing comparable ML-based tools to replace traditional numerical simulation in a timely manner.","PeriodicalId":22252,"journal":{"name":"SPE Journal","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141141695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Resin-coated sand (RCS) is an effective way for controlling post-stimulation proppant flowback. However, with the shift to slickwater treatment fluids, the “tail-in” placement approach has proved to be less efficient for complete flowback control due to the proppant settling characteristics of using low-viscosity fluids. A new RCS placement approach was developed based on the results of several flowback studies. Trial wells were completed in different US basins with successful results. Proppant flowback samples were collected during different stages of drillout and production from wells using slickwater fluid systems. Thirty-five wells, completed by thirteen different operators, within the Permian and MidCon basins were evaluated. All wells were completed using multiple proppant mesh sizes. A total of 375 flowback samples were collected during the drillout and production phases. The samples were sieved, and the results were fed into an in-house material balance model to determine the percentages of different mesh sizes in the flowback samples. The conclusions were used as guidelines for a new placement approach implemented in multiple new wells to control proppant flowback. The flowback samples ranged from predominantly lead proppant to a similar proportion of the pumped mesh sizes. Not one of the 35 wells had flowback samples containing the majority tail-in mesh size. This supports the early sand dune assumption, suggesting that the early proppant forms dunes near the wellbore and late sand settles over the existing proppant beds. The use of late RCS appears to have a minimal effect on preventing flowback of the early proppant within a stage utilizing slickwater fracturing. Therefore, RCS efficiency to control proppant flowback with the tail-in method is reduced when used in such slickwater stimulations. To seal the different proppant beds, the new approach recommends pumping multiple RCS steps within a stage. The first RCS step is recommended within the first 10–20%, the second sequence within the first 40–60% of proppant volume, and the third as a tail-in. The exact percentages and step design were based on the results of flowback samples from neighboring wells. The implementation of this approach in more than 30 wells resulted in superior flowback control compared to offset control wells. In all trials, the proppant flowback completely stopped within 1 to 7 days of starting production. In this paper, we discuss the drawbacks of the current RCS placement practice while suggesting a new practical approach supported by data. RCS tail-in showed successful flowback control with viscous fracturing fluids and hybrid systems. For slickwater systems, an optimized placement design for RCS throughout the pump schedule provided enhanced flowback control compared to RCS tail-in. Finally, we illustrate the results of field trials in which utilizing the new RCS placement approach successfully reduced flowback.
{"title":"Novel Resin-Coated Sand Placement Design Guidelines for Controlling Proppant Flowback Post-Slickwater Hydraulic Fracturing Treatments","authors":"Mohamed Tarek, Jada Leung","doi":"10.2118/217830-pa","DOIUrl":"https://doi.org/10.2118/217830-pa","url":null,"abstract":"\u0000 Resin-coated sand (RCS) is an effective way for controlling post-stimulation proppant flowback. However, with the shift to slickwater treatment fluids, the “tail-in” placement approach has proved to be less efficient for complete flowback control due to the proppant settling characteristics of using low-viscosity fluids. A new RCS placement approach was developed based on the results of several flowback studies. Trial wells were completed in different US basins with successful results.\u0000 Proppant flowback samples were collected during different stages of drillout and production from wells using slickwater fluid systems. Thirty-five wells, completed by thirteen different operators, within the Permian and MidCon basins were evaluated. All wells were completed using multiple proppant mesh sizes. A total of 375 flowback samples were collected during the drillout and production phases. The samples were sieved, and the results were fed into an in-house material balance model to determine the percentages of different mesh sizes in the flowback samples. The conclusions were used as guidelines for a new placement approach implemented in multiple new wells to control proppant flowback.\u0000 The flowback samples ranged from predominantly lead proppant to a similar proportion of the pumped mesh sizes. Not one of the 35 wells had flowback samples containing the majority tail-in mesh size. This supports the early sand dune assumption, suggesting that the early proppant forms dunes near the wellbore and late sand settles over the existing proppant beds. The use of late RCS appears to have a minimal effect on preventing flowback of the early proppant within a stage utilizing slickwater fracturing. Therefore, RCS efficiency to control proppant flowback with the tail-in method is reduced when used in such slickwater stimulations. To seal the different proppant beds, the new approach recommends pumping multiple RCS steps within a stage. The first RCS step is recommended within the first 10–20%, the second sequence within the first 40–60% of proppant volume, and the third as a tail-in. The exact percentages and step design were based on the results of flowback samples from neighboring wells. The implementation of this approach in more than 30 wells resulted in superior flowback control compared to offset control wells. In all trials, the proppant flowback completely stopped within 1 to 7 days of starting production.\u0000 In this paper, we discuss the drawbacks of the current RCS placement practice while suggesting a new practical approach supported by data. RCS tail-in showed successful flowback control with viscous fracturing fluids and hybrid systems. For slickwater systems, an optimized placement design for RCS throughout the pump schedule provided enhanced flowback control compared to RCS tail-in. Finally, we illustrate the results of field trials in which utilizing the new RCS placement approach successfully reduced flowback.","PeriodicalId":22252,"journal":{"name":"SPE Journal","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141041440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Senhan Hou, Daihong Gu, Daoyong Yang, Shikai Yang, Min Zhao
For this paper, integrated techniques have been developed to optimize the performance of the hybrid steam-solvent injection processes in a depleted post-cold heavy oil production with sand (CHOPS) reservoir with consideration of wormhole networks and foamy oil behavior. After a reservoir geological model has been built and calibrated with the measured production profiles, its wormhole network is inversely determined using the newly developed pressure-gradient-based (PGB) sand failure criterion. Such a calibrated reservoir geological model is then used to maximize the net present value (NPV) of a hybrid steam-solvent injection process by selecting injection time, soaking time, production time, injection rate, steam temperature, and steam quality as the controlling variables. The genetic algorithm (GA) has been integrated with orthogonal array (OA) and Tabu search to maximize the NPV by delaying the displacement front as well as extending the reservoir life under various strategies. Considering the wormhole network and foamy oil behavior and using the NPV as the objective function, such a modified algorithm can be used to allocate and optimize the production-injection strategies of each huff ‘n’ puff (HnP) cycle in a post-CHOPS reservoir with altered porosity and increased permeability within a unified, consistent, and efficient framework.
{"title":"Integrated Optimization of Hybrid Steam-Solvent Injection in Post-CHOPS Reservoirs with Consideration of Wormhole Networks and Foamy Oil Behavior","authors":"Senhan Hou, Daihong Gu, Daoyong Yang, Shikai Yang, Min Zhao","doi":"10.2118/212145-pa","DOIUrl":"https://doi.org/10.2118/212145-pa","url":null,"abstract":"\u0000 For this paper, integrated techniques have been developed to optimize the performance of the hybrid steam-solvent injection processes in a depleted post-cold heavy oil production with sand (CHOPS) reservoir with consideration of wormhole networks and foamy oil behavior. After a reservoir geological model has been built and calibrated with the measured production profiles, its wormhole network is inversely determined using the newly developed pressure-gradient-based (PGB) sand failure criterion. Such a calibrated reservoir geological model is then used to maximize the net present value (NPV) of a hybrid steam-solvent injection process by selecting injection time, soaking time, production time, injection rate, steam temperature, and steam quality as the controlling variables. The genetic algorithm (GA) has been integrated with orthogonal array (OA) and Tabu search to maximize the NPV by delaying the displacement front as well as extending the reservoir life under various strategies. Considering the wormhole network and foamy oil behavior and using the NPV as the objective function, such a modified algorithm can be used to allocate and optimize the production-injection strategies of each huff ‘n’ puff (HnP) cycle in a post-CHOPS reservoir with altered porosity and increased permeability within a unified, consistent, and efficient framework.","PeriodicalId":22252,"journal":{"name":"SPE Journal","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141048408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ida Bagus Gede Hermawan Manuaba, Mohammad Aljishi, Marie Van Steene, James Dolan
The electromagnetic propagation (EMP) measurement frequently acquired with logging-while-drilling (LWD) tools in high-angle wells is sensitive to geometrical effects that can mask the true formation resistivity. Less commonly used, the LWD laterolog measurement is sometimes perceived as providing data too shallow to give a true formation resistivity (Rt). In this paper, we presents modeling and actual examples to demonstrate that the laterolog can often provide a superior resistivity measurement for formation evaluation to that of the LWD EMP tool. We examine the laterolog and EMP resistivities in several high-angle wells crossing carbonate formations in 8.5-in. and 6.125-in. hole sizes. In the 8.5-in. sections, producers and water injectors (high- and low-resistivity ranges) were evaluated. In the 6.125-in. sections, one reservoir sandwiched between two very high-resistivity layers and another borehole in a highly fractured reservoir were examined. The laterolog data were corrected for invasion using a 1D inversion of the memory data. Structure-based forward modeling was used to examine and explain the differences between the laterolog and EMP resistivity measurements. In the first example in a thick low-resistivity water reservoir, laterolog resistivity and EMP resistivity agree, showing that the two tools provide the same measurement when no geometrical effects are present. In the first part of the second example, a reservoir zone was initially drilled only with the LWD EMP resistivity measurement. The LWD laterolog was run several days later, and the resistivity data read much lower in the relogged section compared with the EMP resistivity. The laterolog 1D inversion was unable to resolve Rt because of the excessively deep invasion that occurred over the course of several days. In the second part of the second example, the laterolog resistivity showed a clear conductive invasion profile. While the deepest laterolog real-time resistivity data indicated lower resistivity than the EMP resistivity, the true resistivity, Rt (invasion-corrected 1D-inverted laterolog resistivity), matched the EMP Rt resistivity. This result validated both measurements and emphasized that the differences were due to invasion. The first two examples demonstrated that when acquired in normal drilling conditions (within 1–2 hours of drilling the section), the laterolog measurements can provide uninvaded formation resistivity even in the presence of invasion. A reservoir in another example was sandwiched between resistive layers that caused difficult-to-explain elevated EMP resistivity readings. Structural modeling reproduced the elevated behavior of the EMP data and explained the differences between resistivity measurements. This result showed that the laterolog is better suited to evaluate resistivity in thin reservoirs where there is a high-resistivity contrast to the adjacent layer. Finally, fractured reservoir examples are presented, which show that both th
{"title":"Logging-While-Drilling Laterolog vs. Electromagnetic Propagation Measurements: Which Is Telling the True Resistivity?","authors":"Ida Bagus Gede Hermawan Manuaba, Mohammad Aljishi, Marie Van Steene, James Dolan","doi":"10.2118/219772-pa","DOIUrl":"https://doi.org/10.2118/219772-pa","url":null,"abstract":"\u0000 The electromagnetic propagation (EMP) measurement frequently acquired with logging-while-drilling (LWD) tools in high-angle wells is sensitive to geometrical effects that can mask the true formation resistivity. Less commonly used, the LWD laterolog measurement is sometimes perceived as providing data too shallow to give a true formation resistivity (Rt). In this paper, we presents modeling and actual examples to demonstrate that the laterolog can often provide a superior resistivity measurement for formation evaluation to that of the LWD EMP tool.\u0000 We examine the laterolog and EMP resistivities in several high-angle wells crossing carbonate formations in 8.5-in. and 6.125-in. hole sizes. In the 8.5-in. sections, producers and water injectors (high- and low-resistivity ranges) were evaluated. In the 6.125-in. sections, one reservoir sandwiched between two very high-resistivity layers and another borehole in a highly fractured reservoir were examined. The laterolog data were corrected for invasion using a 1D inversion of the memory data. Structure-based forward modeling was used to examine and explain the differences between the laterolog and EMP resistivity measurements.\u0000 In the first example in a thick low-resistivity water reservoir, laterolog resistivity and EMP resistivity agree, showing that the two tools provide the same measurement when no geometrical effects are present.\u0000 In the first part of the second example, a reservoir zone was initially drilled only with the LWD EMP resistivity measurement. The LWD laterolog was run several days later, and the resistivity data read much lower in the relogged section compared with the EMP resistivity. The laterolog 1D inversion was unable to resolve Rt because of the excessively deep invasion that occurred over the course of several days.\u0000 In the second part of the second example, the laterolog resistivity showed a clear conductive invasion profile. While the deepest laterolog real-time resistivity data indicated lower resistivity than the EMP resistivity, the true resistivity, Rt (invasion-corrected 1D-inverted laterolog resistivity), matched the EMP Rt resistivity. This result validated both measurements and emphasized that the differences were due to invasion.\u0000 The first two examples demonstrated that when acquired in normal drilling conditions (within 1–2 hours of drilling the section), the laterolog measurements can provide uninvaded formation resistivity even in the presence of invasion.\u0000 A reservoir in another example was sandwiched between resistive layers that caused difficult-to-explain elevated EMP resistivity readings. Structural modeling reproduced the elevated behavior of the EMP data and explained the differences between resistivity measurements. This result showed that the laterolog is better suited to evaluate resistivity in thin reservoirs where there is a high-resistivity contrast to the adjacent layer.\u0000 Finally, fractured reservoir examples are presented, which show that both th","PeriodicalId":22252,"journal":{"name":"SPE Journal","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141049866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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