Breidablikk is a green field on the Norwegian Continental Shelf that just started the preproduction drilling of 23 wells in two structures. We have two reservoir fluid samples from exploration wells in each structure with relatively high viscosity of 4 and 8 cP, respectively. Our dynamic reservoir simulations on the Breidablikk Field indicate that any change in the viscosity in each direction can lead to a 20 to 30% difference in oil recovery. Therefore, updating our reservoir models with the viscosity distribution in the field along with the drilling activities is important. Currently, our models assume homogeneous reservoir oil viscosities across each structure. In this study, our primary aim is to conduct a holistic evaluation of the reservoir oil viscosity, using multiple methods to determine the most effective approach for qualitatively mapping the oil viscosity across the field, distinguishing between the low- and high-viscosity regions. The technologies chosen for this assessment are standard mud gas data, advanced mud gas data, and analysis of oil extracts from cuttings, given they have previously demonstrated their capability to estimate fluid properties while drilling or within a limited time frame, as evidenced by the work of Cutler et al. (2022). The methods were compared using pressure/volume/temperature (PVT) measurements as a benchmark. As of today, this method is considered the most reliable to obtain reservoir fluid properties, and in consequence, these measurements serve as the reference viscosity values in the study. The results of our analysis in Breidablikk show that an approach based on advanced mud gas data provide an oil quality classification that distinguishes between high- and low-viscosity reservoir oils, using the ethane/n-pentane ratio as the best parameter correlated to reservoir oil viscosity in Breidablikk. The threshold for the two viscosity regions is identified from a reservoir fluid database from the Breidablikk-Grane area, and the oil viscosity region estimated from advanced mud gas data agrees well with the PVT measurements. The viscosity estimation using a standard mud gas approach based on methane to propane compositions indicates that this technology cannot correctly differentiate between low- and high-viscosity region wells in the Breidablikk Field. Hence, it is not recommended. Further findings from our analysis indicate that the utilization of oil-based mud, combined with a high drilling speed, significantly affects the quality of the cuttings in Breidablikk. Consequently, the application of traditional geochemical analysis methods on cutting extracts is challenging. Therefore, this method is not recommended for the qualitative identification of the viscosity region of a given well. Benchmarking all available technologies allows us to select a real-time, reliable, and cost-efficient method to qualitatively estimate reservoir oil viscosity in Breidablikk. The selected method is field-specific and not ge
Breidablikk是挪威大陆架上的一片绿地,刚刚开始在两个结构中进行23口井的预生产钻井。我们在每个构造中都有两个探井的储层流体样品,粘度相对较高,分别为4和8 cP。我们对Breidablikk油田的动态油藏模拟表明,在每个方向上粘度的任何变化都会导致原油采收率的20%到30%的差异。因此,随着钻井活动的进行,根据油田的粘度分布来更新储层模型是很重要的。目前,我们的模型假设每个结构的油藏粘度都是均匀的。在这项研究中,我们的主要目的是对储层油粘度进行全面评估,使用多种方法确定最有效的方法来定性绘制整个油田的油粘度,区分低粘度区和高粘度区。本次评估选择的技术包括标准泥浆气数据、高级泥浆气数据和岩屑油提取物分析,因为这些技术之前已经证明了它们能够在钻井过程中或在有限的时间内估计流体性质,正如Cutler等人(2022)的工作所证明的那样。以压力/体积/温度(PVT)测量作为基准,对两种方法进行了比较。迄今为止,这种方法被认为是获得储层流体性质最可靠的方法,因此,这些测量结果可以作为研究中的参考粘度值。我们在Breidablikk的分析结果表明,基于先进的泥浆气数据的方法提供了一种区分高粘度和低粘度油藏油的油质分类方法,使用乙烷/正戊烷比作为与Breidablikk油藏油粘度相关的最佳参数。根据Breidablikk-Grane地区的储层流体数据库确定了这两个粘度区域的阈值,根据先进的泥浆气数据估计的油粘度区域与PVT测量结果吻合得很好。使用基于甲烷和丙烷组成的标准泥浆气方法进行粘度估算表明,该技术无法正确区分Breidablikk油田的低粘度和高粘度区域井。因此,不建议这样做。进一步的分析结果表明,油基泥浆的使用,加上高钻井速度,显著影响了Breidablikk钻井岩屑的质量。因此,传统的地球化学分析方法对切削提取物的应用具有挑战性。因此,不建议用这种方法对给定井的粘度区进行定性鉴定。通过对所有可用技术进行基准测试,我们可以选择一种实时、可靠、经济的方法来定性地估计Breidablikk油田的油藏油粘度。所选择的方法是针对特定油田的,并不适用于其他稠油油田。综上所述,在油田开发的早期阶段提供准确的油藏油粘度图对于进一步优化钻井目标并最终提高采收率至关重要(Halvorsen等,2016;Maraj et al., 2021)。
{"title":"Holistic Evaluation of Reservoir Oil Viscosity in Breidablikk Field – Including Mud Gas Logging Approach","authors":"A. Cely, Ingvar Skaar, Tao Yang","doi":"10.30632/pjv64n6-2023a8","DOIUrl":"https://doi.org/10.30632/pjv64n6-2023a8","url":null,"abstract":"Breidablikk is a green field on the Norwegian Continental Shelf that just started the preproduction drilling of 23 wells in two structures. We have two reservoir fluid samples from exploration wells in each structure with relatively high viscosity of 4 and 8 cP, respectively. Our dynamic reservoir simulations on the Breidablikk Field indicate that any change in the viscosity in each direction can lead to a 20 to 30% difference in oil recovery. Therefore, updating our reservoir models with the viscosity distribution in the field along with the drilling activities is important. Currently, our models assume homogeneous reservoir oil viscosities across each structure. In this study, our primary aim is to conduct a holistic evaluation of the reservoir oil viscosity, using multiple methods to determine the most effective approach for qualitatively mapping the oil viscosity across the field, distinguishing between the low- and high-viscosity regions. The technologies chosen for this assessment are standard mud gas data, advanced mud gas data, and analysis of oil extracts from cuttings, given they have previously demonstrated their capability to estimate fluid properties while drilling or within a limited time frame, as evidenced by the work of Cutler et al. (2022). The methods were compared using pressure/volume/temperature (PVT) measurements as a benchmark. As of today, this method is considered the most reliable to obtain reservoir fluid properties, and in consequence, these measurements serve as the reference viscosity values in the study. The results of our analysis in Breidablikk show that an approach based on advanced mud gas data provide an oil quality classification that distinguishes between high- and low-viscosity reservoir oils, using the ethane/n-pentane ratio as the best parameter correlated to reservoir oil viscosity in Breidablikk. The threshold for the two viscosity regions is identified from a reservoir fluid database from the Breidablikk-Grane area, and the oil viscosity region estimated from advanced mud gas data agrees well with the PVT measurements. The viscosity estimation using a standard mud gas approach based on methane to propane compositions indicates that this technology cannot correctly differentiate between low- and high-viscosity region wells in the Breidablikk Field. Hence, it is not recommended. Further findings from our analysis indicate that the utilization of oil-based mud, combined with a high drilling speed, significantly affects the quality of the cuttings in Breidablikk. Consequently, the application of traditional geochemical analysis methods on cutting extracts is challenging. Therefore, this method is not recommended for the qualitative identification of the viscosity region of a given well. Benchmarking all available technologies allows us to select a real-time, reliable, and cost-efficient method to qualitatively estimate reservoir oil viscosity in Breidablikk. The selected method is field-specific and not ge","PeriodicalId":170688,"journal":{"name":"Petrophysics – The SPWLA Journal of Formation Evaluation and Reservoir Description","volume":"41 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138626438","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}
Tom Bradley, Simon Austin, David Holbrough, Warren Fernandes, Xuandong Wang, Gleb Dyatlov, Arnt H. Veenstra
This paper describes a proposed high-specification standard format that is ideally suited for the data management of definitive records of wellbore logs. For this reason, it is a good standard for data exchange between applications. The format is suitable for complex three-dimensional (3D) data, including those generated by deep azimuthal resistivity (DAR) and ultradeep azimuthal resistivity (UDAR) tools, acoustic borehole reflection images, vertical seismic profiles (VSP), borehole imaging tools, multifingered caliper logs, and array data with multiple depths of investigation. It is applicable for use with logging-while-drilling (LWD) and wireline-conveyed logging tools. The format also naturally collapses down when utilized to store simple conventional logs that contain one value per depth in the wellbore. The proposed format provides spatial details of every data point collected by or interpreted from a wellbore-logging tool. The position of each data point is defined by reference back to the measure point of the sonde, which in turn is defined by the wellbore deviation survey and its coordinate reference system (CRS). Each data point in space may have an unrestricted number of parameters. An example might be most likely horizontal and vertical resistivity, maximum value based on uncertainty, minimum value based on uncertainty, and flags indicating the data position with respect to depth of detection (DOD). The new proposed format is so versatile. It is suitable as an Open Group Open Subsurface Data UniverseTM (OSDUTM) standard to store and exchange all data measured by logging tools in a wellbore and can possibly be extended to include all well data (for example, core, cuttings, and more). The proposed format requires a detailed definition so that computer scientists can implement it in applications used for subsurface modeling. The OSDU will also require this detailed definition in order to adopt it as a standard.
本文介绍了一种高规格的标准格式,它非常适合于井筒测井最终记录的数据管理。由于这个原因,它是应用程序之间数据交换的良好标准。该格式适用于复杂的三维(3D)数据,包括由深方位角电阻率(DAR)和超深方位角电阻率(UDAR)工具、井眼声波反射图像、垂直地震剖面(VSP)、井眼成像工具、多指井径测井以及多个深度的阵列数据生成的数据。它适用于随钻测井(LWD)和电缆输送测井工具。当用于存储井筒中每个深度只包含一个值的简单常规测井数据时,这种格式自然也会失效。该格式提供了由测井工具收集或解释的每个数据点的空间细节。每个数据点的位置都是通过参考回测仪的测点来定义的,测点又由井斜测量及其坐标参考系统(CRS)来定义。空间中的每个数据点可以有无限制数量的参数。最可能的例子是水平和垂直电阻率,基于不确定性的最大值,基于不确定性的最小值,以及指示相对于探测深度(DOD)的数据位置的标志。新提议的格式是如此通用。它适合作为Open Group Open Subsurface Data UniverseTM (OSDUTM)标准,用于存储和交换测井工具在井筒中测量的所有数据,并且可以扩展到包括所有井数据(例如岩心、岩屑等)。提出的格式需要一个详细的定义,以便计算机科学家可以在用于地下建模的应用程序中实现它。OSDU还需要这个详细的定义,以便将其作为标准采用。
{"title":"A Universal Data Format for Wellbore Logs","authors":"Tom Bradley, Simon Austin, David Holbrough, Warren Fernandes, Xuandong Wang, Gleb Dyatlov, Arnt H. Veenstra","doi":"10.30632/pjv64n6-2023a1","DOIUrl":"https://doi.org/10.30632/pjv64n6-2023a1","url":null,"abstract":"This paper describes a proposed high-specification standard format that is ideally suited for the data management of definitive records of wellbore logs. For this reason, it is a good standard for data exchange between applications. The format is suitable for complex three-dimensional (3D) data, including those generated by deep azimuthal resistivity (DAR) and ultradeep azimuthal resistivity (UDAR) tools, acoustic borehole reflection images, vertical seismic profiles (VSP), borehole imaging tools, multifingered caliper logs, and array data with multiple depths of investigation. It is applicable for use with logging-while-drilling (LWD) and wireline-conveyed logging tools. The format also naturally collapses down when utilized to store simple conventional logs that contain one value per depth in the wellbore. The proposed format provides spatial details of every data point collected by or interpreted from a wellbore-logging tool. The position of each data point is defined by reference back to the measure point of the sonde, which in turn is defined by the wellbore deviation survey and its coordinate reference system (CRS). Each data point in space may have an unrestricted number of parameters. An example might be most likely horizontal and vertical resistivity, maximum value based on uncertainty, minimum value based on uncertainty, and flags indicating the data position with respect to depth of detection (DOD). The new proposed format is so versatile. It is suitable as an Open Group Open Subsurface Data UniverseTM (OSDUTM) standard to store and exchange all data measured by logging tools in a wellbore and can possibly be extended to include all well data (for example, core, cuttings, and more). The proposed format requires a detailed definition so that computer scientists can implement it in applications used for subsurface modeling. The OSDU will also require this detailed definition in order to adopt it as a standard.","PeriodicalId":170688,"journal":{"name":"Petrophysics – The SPWLA Journal of Formation Evaluation and Reservoir Description","volume":" 30","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138616128","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 : 2023-12-01DOI: 10.30632/pjv64n6-2023a11
Jie Wang, Christine Ehlig-Economides
Dissolution of CO2 in saline waters is considered one of three main CO2 trapping mechanisms, along with structural/stratigraphic trapping and mineralization. CO2 can dissolve in fresh/saline water under typical reservoir pressure and temperatures. Its solubility is dependent on pressure, temperature, and salinity. CO2 solubility studies typically consider saline water or fresh water as a liquid without any predissolved gases. The reality is formation water may contain appreciable dissolved gases for all pressure and temperature conditions. An example of gas-water ratio (GWR) can be ~1 scf/stb for formation water in an oil reservoir and ~5 to 6 scf/stb for a deep saline aquifer. Therefore, it is essential to quantify the effect of brine salinity on CO2 solubility in “live” saline waters. Just as “live” oil denotes reservoir oil that contains solution gas, we define “live” brine as saline water that includes dissolved gases. Conversely, “dead” brine refers to saline water devoid of any dissolved gas content. Two sets of experiments were conducted under typical reservoir conditions. The first set of experiments evaluated the CO2 solubility in live formation water. The second set of experiments evaluated how variation in the live brine salinity affected CO2 solubility. These experiments involved 1) synthesis of the brine, 2) synthesis of natural gas mixture, 3) recombination of live formation water with a natural gas mixture and transfer into a high-pressure and high-temperature pressure-volume-temperature (PVT) visual cell, 4) CO2 addition to the PVT cell, and 5) bubblepoint pressure determination within the PVT cell. The results showed that CO2 solubility in live formation water is significantly less than that in “dead” water under reservoir conditions. In addition, the brine salinity affects CO2 solubility in live formation water by further reducing CO2 solubility with increasing live brine salinity. As the brine salinity increases, very little CO2 can be dissolved in the live brine once it reaches a certain solubility. An understanding of CO2 dissolution in live saline water is essential for future CCUS evaluation and execution.
{"title":"Effect of Predisolved Natural Gas on CO2 Solubility in Water With Various Salinities at Reservoir Conditions","authors":"Jie Wang, Christine Ehlig-Economides","doi":"10.30632/pjv64n6-2023a11","DOIUrl":"https://doi.org/10.30632/pjv64n6-2023a11","url":null,"abstract":"Dissolution of CO2 in saline waters is considered one of three main CO2 trapping mechanisms, along with structural/stratigraphic trapping and mineralization. CO2 can dissolve in fresh/saline water under typical reservoir pressure and temperatures. Its solubility is dependent on pressure, temperature, and salinity. CO2 solubility studies typically consider saline water or fresh water as a liquid without any predissolved gases. The reality is formation water may contain appreciable dissolved gases for all pressure and temperature conditions. An example of gas-water ratio (GWR) can be ~1 scf/stb for formation water in an oil reservoir and ~5 to 6 scf/stb for a deep saline aquifer. Therefore, it is essential to quantify the effect of brine salinity on CO2 solubility in “live” saline waters. Just as “live” oil denotes reservoir oil that contains solution gas, we define “live” brine as saline water that includes dissolved gases. Conversely, “dead” brine refers to saline water devoid of any dissolved gas content. Two sets of experiments were conducted under typical reservoir conditions. The first set of experiments evaluated the CO2 solubility in live formation water. The second set of experiments evaluated how variation in the live brine salinity affected CO2 solubility. These experiments involved 1) synthesis of the brine, 2) synthesis of natural gas mixture, 3) recombination of live formation water with a natural gas mixture and transfer into a high-pressure and high-temperature pressure-volume-temperature (PVT) visual cell, 4) CO2 addition to the PVT cell, and 5) bubblepoint pressure determination within the PVT cell. The results showed that CO2 solubility in live formation water is significantly less than that in “dead” water under reservoir conditions. In addition, the brine salinity affects CO2 solubility in live formation water by further reducing CO2 solubility with increasing live brine salinity. As the brine salinity increases, very little CO2 can be dissolved in the live brine once it reaches a certain solubility. An understanding of CO2 dissolution in live saline water is essential for future CCUS evaluation and execution.","PeriodicalId":170688,"journal":{"name":"Petrophysics – The SPWLA Journal of Formation Evaluation and Reservoir Description","volume":" 91","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138620553","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}
We study the impact of signal-to-noise ratio (SNR) on nuclear magnetic resonance (NMR) T1-T2 maps across data sets acquired in multiple wells of an unconventional field under various logging and processing conditions. The mean and standard deviation of NMR porosity error between continuous moving-pass and stationary measurements are used to obtain insights into the impact of SNR on accuracy and precision. In a proof-of-concept experiment, we introduce a novel semi-analytical smeared-peak (SASP) technique that compensates for the over-regularized smearing due to poor SNR, of T1-T2 relaxation responses of different fluids. The SASP approximation to de-smear volumes of different fluid types is validated with field measurements from multiple wells. The uplift of the SASP technique in improving fluid volume interpretations is apparent in the in-situ calibration of low-SNR moving-pass NMR measurements with high-quality stationary measurements. The learnings show that logging protocols that are designed to increase SNR by combining specific acquisition parameters with processing strategies, within acceptable compromises, are mandatory for reliable NMR characterization of unconventional reservoirs.
{"title":"Learnings From Impact and Implications of Signal-To-Noise in NMR T1-T2 Logging of Unconventional Reservoirs","authors":"Olabode Ijasan","doi":"10.30632/pjv64n6-2023a4","DOIUrl":"https://doi.org/10.30632/pjv64n6-2023a4","url":null,"abstract":"We study the impact of signal-to-noise ratio (SNR) on nuclear magnetic resonance (NMR) T1-T2 maps across data sets acquired in multiple wells of an unconventional field under various logging and processing conditions. The mean and standard deviation of NMR porosity error between continuous moving-pass and stationary measurements are used to obtain insights into the impact of SNR on accuracy and precision. In a proof-of-concept experiment, we introduce a novel semi-analytical smeared-peak (SASP) technique that compensates for the over-regularized smearing due to poor SNR, of T1-T2 relaxation responses of different fluids. The SASP approximation to de-smear volumes of different fluid types is validated with field measurements from multiple wells. The uplift of the SASP technique in improving fluid volume interpretations is apparent in the in-situ calibration of low-SNR moving-pass NMR measurements with high-quality stationary measurements. The learnings show that logging protocols that are designed to increase SNR by combining specific acquisition parameters with processing strategies, within acceptable compromises, are mandatory for reliable NMR characterization of unconventional reservoirs.","PeriodicalId":170688,"journal":{"name":"Petrophysics – The SPWLA Journal of Formation Evaluation and Reservoir Description","volume":" 61","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138612223","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}
M. Bennis, Tarek S. Mohamed, C. Torres‐Verdín, G. Merletti, Camilo Gelvez
Formation pressure/fluid measurements are impacted by mud-filtrate invasion, which may require long fluid pumpout durations to acquire hydrocarbon samples with minimal mud-filtrate contamination. However, unlike other well-logging instruments, formation testers do not have a fixed depth of investigation that limits their ability to pump out mud filtrate until acquiring original formation fluids (i.e., sensing the uninvaded zone). We use an in-house petrophysical and fluid-flow simulator to perform numerical simulations of mud-filtrate invasion, well logs, and formation-tester measurements to estimate the radial distance of invasion and the corresponding radial profile of water saturation. Numerical simulations are initialized with the construction of a multilayer petrophysical model. Initial guesses of volumetric concentration of shale, porosity, water saturation, irreducible water saturation, and residual hydrocarbon saturation are obtained from conventional petrophysical interpretation. Fluid-flow-dependent petrophysical properties (permeability, capillary pressure, and relative permeability), mud properties, rock mineral composition, and in-situ fluid properties are obtained from laboratory measurements. The process of mud-filtrate invasion and the corresponding resistivity and nuclear logs are numerically simulated to iteratively match the available well logs and estimate layer-by-layer formation water saturation. Next, using our multiphase formation testing simulator, we numerically simulate actual fluid sampling operations performed with a dual-packer formation tester. Finally, we estimate irreducible water saturation by minimizing the difference between the hydrocarbon breakthrough time numerically simulated and measured with formation-tester measurements. The examined sandstone reservoir is characterized by low porosity (up to 0.14), low-to-medium permeability (up to 40 md), and high residual gas saturation (between 0.4 and 0.5). The deep mud-filtrate invasion resulted from extended overbalanced exposure to high-salinity water-based mud (17 days of invasion and 1,800 psi overbalance pressure) coupled with the low mud-filtrate storage capacity of tight sandstones. Therefore, the uninvaded formation is located far beyond the depth of investigation of resistivity tools, whereby deep-sensing resistivities are lower than those of uninvaded formation resistivity. Through the numerical simulation of mud-filtrate invasion, well logs, and formation-tester measurements, we estimated radial and vertical distributions of water saturation around the borehole. Likewise, we quantified the hydrocarbon breakthrough time, which matched field measurements of 6.5 hours. The estimated radius of invasion was approximately 2.5 m, while the difference between estimated water saturation in the uninvaded zone and water saturation estimated from the deep-sensing resistivity log was approximately 0.13, therefore improving the estimation of the original gas in place.
{"title":"Assessment of Depth of Mud-Filtrate Invasion and Water Saturation Using Formation-Tester Measurements: Application to Deeply Invaded Tight-Gas Sandstones","authors":"M. Bennis, Tarek S. Mohamed, C. Torres‐Verdín, G. Merletti, Camilo Gelvez","doi":"10.30632/pjv64n6-2023a9","DOIUrl":"https://doi.org/10.30632/pjv64n6-2023a9","url":null,"abstract":"Formation pressure/fluid measurements are impacted by mud-filtrate invasion, which may require long fluid pumpout durations to acquire hydrocarbon samples with minimal mud-filtrate contamination. However, unlike other well-logging instruments, formation testers do not have a fixed depth of investigation that limits their ability to pump out mud filtrate until acquiring original formation fluids (i.e., sensing the uninvaded zone). We use an in-house petrophysical and fluid-flow simulator to perform numerical simulations of mud-filtrate invasion, well logs, and formation-tester measurements to estimate the radial distance of invasion and the corresponding radial profile of water saturation. Numerical simulations are initialized with the construction of a multilayer petrophysical model. Initial guesses of volumetric concentration of shale, porosity, water saturation, irreducible water saturation, and residual hydrocarbon saturation are obtained from conventional petrophysical interpretation. Fluid-flow-dependent petrophysical properties (permeability, capillary pressure, and relative permeability), mud properties, rock mineral composition, and in-situ fluid properties are obtained from laboratory measurements. The process of mud-filtrate invasion and the corresponding resistivity and nuclear logs are numerically simulated to iteratively match the available well logs and estimate layer-by-layer formation water saturation. Next, using our multiphase formation testing simulator, we numerically simulate actual fluid sampling operations performed with a dual-packer formation tester. Finally, we estimate irreducible water saturation by minimizing the difference between the hydrocarbon breakthrough time numerically simulated and measured with formation-tester measurements. The examined sandstone reservoir is characterized by low porosity (up to 0.14), low-to-medium permeability (up to 40 md), and high residual gas saturation (between 0.4 and 0.5). The deep mud-filtrate invasion resulted from extended overbalanced exposure to high-salinity water-based mud (17 days of invasion and 1,800 psi overbalance pressure) coupled with the low mud-filtrate storage capacity of tight sandstones. Therefore, the uninvaded formation is located far beyond the depth of investigation of resistivity tools, whereby deep-sensing resistivities are lower than those of uninvaded formation resistivity. Through the numerical simulation of mud-filtrate invasion, well logs, and formation-tester measurements, we estimated radial and vertical distributions of water saturation around the borehole. Likewise, we quantified the hydrocarbon breakthrough time, which matched field measurements of 6.5 hours. The estimated radius of invasion was approximately 2.5 m, while the difference between estimated water saturation in the uninvaded zone and water saturation estimated from the deep-sensing resistivity log was approximately 0.13, therefore improving the estimation of the original gas in place.","PeriodicalId":170688,"journal":{"name":"Petrophysics – The SPWLA Journal of Formation Evaluation and Reservoir Description","volume":"4 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138626126","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}
In the current scenario of project management, where the agility and optimization of operations have been prioritized, the practice of logging while drilling (LWD) has gained space compared to traditional wireline logging. In theory, acquiring quality petrophysical properties during drilling brings greater agility in decision making about completion and optimizes operation costs. However, regarding borehole image logs, due to limitations in transmission capacity, the actual available data in real time contain about 50% (for resistivity images) of the full azimuth information, being insufficient for the identification of critical geological structures capable of impacting the communication between production or injection zones or the quality of cementation, such as fractures, caves, and geomechanical collapse zones. The tool’s memory data with the full information may take a few days after the end of drilling to be delivered by the service company, which in some cases is not enough for fast decision making regarding completion. In this work, we tested models based on generative adversarial neural networks (GANs) to reconstruct the complete memory data based on real-time input. As in conventional GAN schemes, a generator is trained to receive a real-time input and create a “memory-like” image, while a discriminator is trained to tell real and fake images apart. To regularize the convergence of training, we used an architecture known in the literature as CycleGAN, where another generator-discriminator pair is trained simultaneously to do the reverse process, recreating the real-time data. Variations of the training process and data sets were used to generate different CycleGAN models. They were trained using logs of presalt reservoirs in Buzios Field, and performance was assessed on logging intervals not seen by the algorithms during training. The results achieved so far have been very promising, as in certain intervals, resultant models were able to capture the presence of fractures and caves. This methodology represents a way of circumventing telemetry limitations, where missing information is added indirectly to the real-time data as the artificial intelligence (AI) algorithm learns the main characteristics of a field/reservoir. Therefore, previous knowledge from the field can be used to continuously optimize future operations, efficiently incorporating the available database into the workflow of petrophysicists for the recognition of geological and geomechanical structures in time to support decision making in completion operations.
{"title":"Application of GAN to Resolution Enhancement of LWD Real-Time Image Logs to Support Decision Making","authors":"W. Trevizan, Candida Menezes de Jesus","doi":"10.30632/pjv64n6-2023a6","DOIUrl":"https://doi.org/10.30632/pjv64n6-2023a6","url":null,"abstract":"In the current scenario of project management, where the agility and optimization of operations have been prioritized, the practice of logging while drilling (LWD) has gained space compared to traditional wireline logging. In theory, acquiring quality petrophysical properties during drilling brings greater agility in decision making about completion and optimizes operation costs. However, regarding borehole image logs, due to limitations in transmission capacity, the actual available data in real time contain about 50% (for resistivity images) of the full azimuth information, being insufficient for the identification of critical geological structures capable of impacting the communication between production or injection zones or the quality of cementation, such as fractures, caves, and geomechanical collapse zones. The tool’s memory data with the full information may take a few days after the end of drilling to be delivered by the service company, which in some cases is not enough for fast decision making regarding completion. In this work, we tested models based on generative adversarial neural networks (GANs) to reconstruct the complete memory data based on real-time input. As in conventional GAN schemes, a generator is trained to receive a real-time input and create a “memory-like” image, while a discriminator is trained to tell real and fake images apart. To regularize the convergence of training, we used an architecture known in the literature as CycleGAN, where another generator-discriminator pair is trained simultaneously to do the reverse process, recreating the real-time data. Variations of the training process and data sets were used to generate different CycleGAN models. They were trained using logs of presalt reservoirs in Buzios Field, and performance was assessed on logging intervals not seen by the algorithms during training. The results achieved so far have been very promising, as in certain intervals, resultant models were able to capture the presence of fractures and caves. This methodology represents a way of circumventing telemetry limitations, where missing information is added indirectly to the real-time data as the artificial intelligence (AI) algorithm learns the main characteristics of a field/reservoir. Therefore, previous knowledge from the field can be used to continuously optimize future operations, efficiently incorporating the available database into the workflow of petrophysicists for the recognition of geological and geomechanical structures in time to support decision making in completion operations.","PeriodicalId":170688,"journal":{"name":"Petrophysics – The SPWLA Journal of Formation Evaluation and Reservoir Description","volume":" 83","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138612027","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}
Nuclear logging techniques have played a critical role in the evaluation and surveillance of hydrocarbon reservoirs since the introduction of the gamma ray log in 1939. This paper reviews the history of key developments in nuclear logging that led to improved methods to identify gas-oil (GOC), gas-water (GWC), and oil-water (OWC) contacts in steel-cased wells, as well as methods to identify gas, steam, and waterflood front encroachment, calculate their saturations, and recognize problems in efficient reservoir depletion. This paper will focus solely on nuclear methods used to directly identify fluids behind pipe using natural gamma radiation, neutron-induced gamma radiation, and neutron flux measurements. This includes gamma ray, spectral gamma ray, single- and dual-detector neutron measurements, pulsed-neutron capture, (), and pulsed-neutron spectroscopy (carbon/oxygen or C/O) methods. It will not cover other methods of identifying fluids behind pipe, such as borehole gravity and deep electromagnetic (EM) methods using wired pipe. It also will not cover indirect methods to infer fluid types in reservoirs, such as nuclear production logging using gamma density and pulsed-neutron measurements.
{"title":"Evolution of Casedhole Nuclear Surveillance Logging Through Time","authors":"D. Fitz","doi":"10.30632/pjv64n4-2023a1","DOIUrl":"https://doi.org/10.30632/pjv64n4-2023a1","url":null,"abstract":"Nuclear logging techniques have played a critical role in the evaluation and\u0000 surveillance of hydrocarbon reservoirs since the introduction of the gamma ray log in\u0000 1939. This paper reviews the history of key developments in nuclear logging that led to\u0000 improved methods to identify gas-oil (GOC), gas-water (GWC), and oil-water (OWC)\u0000 contacts in steel-cased wells, as well as methods to identify gas, steam, and waterflood\u0000 front encroachment, calculate their saturations, and recognize problems in efficient\u0000 reservoir depletion. This paper will focus solely on nuclear methods used to directly\u0000 identify fluids behind pipe using natural gamma radiation, neutron-induced gamma\u0000 radiation, and neutron flux measurements. This includes gamma ray, spectral gamma ray,\u0000 single- and dual-detector neutron measurements, pulsed-neutron capture, (), and\u0000 pulsed-neutron spectroscopy (carbon/oxygen or C/O) methods. It will not cover other\u0000 methods of identifying fluids behind pipe, such as borehole gravity and deep\u0000 electromagnetic (EM) methods using wired pipe. It also will not cover indirect methods\u0000 to infer fluid types in reservoirs, such as nuclear production logging using gamma\u0000 density and pulsed-neutron measurements.","PeriodicalId":170688,"journal":{"name":"Petrophysics – The SPWLA Journal of Formation Evaluation and Reservoir Description","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123444167","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}
Yong-hua Chen, Tianhua Zhang, R. Bloemenkamp, Lin Liang
The new-generation, high-definition oil-based mud borehole imagers measure button impedances, which are often inverted to produce images of the formation resistivity, formation permittivity, and sensor standoff. These images, each reflecting a unique aspect of the downhole media, can provide a comprehensive understanding of the reservoir’s secondary porosity, i.e., fractures and vugs. To understand and validate the inversion behavior on fractures and vugs, synthetic logs of axisymmetric 2D fractures and vugs are generated and inverted. While the inverted medium properties follow the variation of the fracture-filling materials, the inverted standoff is shown to be a reliable indication of the fracture open/closed conditions. Specifically, an increased inverted standoff would always appear for mud-filled open fractures, which is further validated by laboratory measurements on artificial fractures and vugs. Numerical tests indicate that mineral-filled fractures may also lead to some variations on the inverted standoff when the resistivity contrast between the mineral-filling material and the host formation is high. Therefore, an elevated standoff may also be associated with a mineral-filled fracture. The modeling and inversion help reveal the connection between the response of the inverted parameters and the actual fracture characteristics. When the fractures are open and filled with mud, the inversion obtains an equivalent standoff at the fractures. This equivalent standoff increases not only with fracture width but also with the resistivity of the host formation. As a result, a fracture may have varying amplitudes in different formation layers. The fracture modeling and inversion also allow us to understand the prevalent existence of conductive fractures observed in the field. It is commonly thought that the resistivity of oil-based mud is always higher than that of the formation. However, this is only true at traditional operating frequencies. Because of mud dispersion, the mud resistivity is different at the two operating frequencies. For an open, mud-filled, resistive fracture to turn conductive, the formation resistivity only needs to exceed the mud resistivity at the higher operating frequency, which is typically on the order of a few 100 Ω·m instead of many 1,000 Ω·m at the lower operating frequency. As a result, an open fracture could be easily conductive in one layer but resistive in another formation layer.
{"title":"Fracture Imaging and Response Characterization of the High-Definition Oil-Based Mud\u0000 Borehole Imagers Through Modeling and Inversion","authors":"Yong-hua Chen, Tianhua Zhang, R. Bloemenkamp, Lin Liang","doi":"10.30632/pjv64n4-2023a4","DOIUrl":"https://doi.org/10.30632/pjv64n4-2023a4","url":null,"abstract":"The new-generation, high-definition oil-based mud borehole imagers measure button\u0000 impedances, which are often inverted to produce images of the formation resistivity,\u0000 formation permittivity, and sensor standoff. These images, each reflecting a unique\u0000 aspect of the downhole media, can provide a comprehensive understanding of the\u0000 reservoir’s secondary porosity, i.e., fractures and vugs. To understand and validate the\u0000 inversion behavior on fractures and vugs, synthetic logs of axisymmetric 2D fractures\u0000 and vugs are generated and inverted. While the inverted medium properties follow the\u0000 variation of the fracture-filling materials, the inverted standoff is shown to be a\u0000 reliable indication of the fracture open/closed conditions. Specifically, an increased\u0000 inverted standoff would always appear for mud-filled open fractures, which is further\u0000 validated by laboratory measurements on artificial fractures and vugs. Numerical tests\u0000 indicate that mineral-filled fractures may also lead to some variations on the inverted\u0000 standoff when the resistivity contrast between the mineral-filling material and the host\u0000 formation is high. Therefore, an elevated standoff may also be associated with a\u0000 mineral-filled fracture. The modeling and inversion help reveal the connection between\u0000 the response of the inverted parameters and the actual fracture characteristics. When\u0000 the fractures are open and filled with mud, the inversion obtains an equivalent standoff\u0000 at the fractures. This equivalent standoff increases not only with fracture width but\u0000 also with the resistivity of the host formation. As a result, a fracture may have\u0000 varying amplitudes in different formation layers. The fracture modeling and inversion\u0000 also allow us to understand the prevalent existence of conductive fractures observed in\u0000 the field. It is commonly thought that the resistivity of oil-based mud is always higher\u0000 than that of the formation. However, this is only true at traditional operating\u0000 frequencies. Because of mud dispersion, the mud resistivity is different at the two\u0000 operating frequencies. For an open, mud-filled, resistive fracture to turn conductive,\u0000 the formation resistivity only needs to exceed the mud resistivity at the higher\u0000 operating frequency, which is typically on the order of a few 100 Ω·m instead of many\u0000 1,000 Ω·m at the lower operating frequency. As a result, an open fracture could be\u0000 easily conductive in one layer but resistive in another formation layer.","PeriodicalId":170688,"journal":{"name":"Petrophysics – The SPWLA Journal of Formation Evaluation and Reservoir Description","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131793000","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}