Pub Date : 2021-05-17DOI: 10.30632/spwla-2021-0065
Xinguang Wang, Dong Li, Lei Zhang, Feng Zhang, Wen-hao Wang, Huiping Gao, China Oilfield Services Limited, Xi 'an HuiNeng Electronic Equipment Co. Ltd
Density logging is a fundamental logging method of open-hole logging series. In cased wells, the formation is usually treated as a cylindrical multiple-layer model including borehole, casing pipe, cement, and original formation, producing more complicated logging response compared to open-hole wells. Several studies have indicated that it is feasible to measure formation density using a density logging tool in cased well under certain conditions, of which the key problem is to determine casing thickness, cement thickness and cement density. This study proposes a novel method to evaluate formation density behind casing using a three-detector density tool. Considering that the backscattered gamma is easily affected by the density behind the casing, especially when the casing thickness is small, a designed ratio of high and low energy window counts of the scattered gamma spectrum is used to calculate casing thickness, which improves the lower limit of the detection. After obtaining casing thickness, the cylindrical multiple-layer model of cased well can be simplified to a cylindrical three-layer model, consisting of cased borehole, cement, and the original formation. Subsequently, the analytical expressions of the thickness of the middle layer (cement) as well as the density of the outer layer (original formation) can be derived based on the logging geometric factor concept, G, which borrowing from electric logging. Consequently, the cement thickness and original formation density could be calculated independently. To demonstrate the feasibility of the proposed method, experimental data are measured in a group of calibration wells. The data processing results show that the proposed analytical model fit well with the experimental data. In addition, the application conditions of the novel method are discussed based on experimental data. Finally, several log examples illustrate that under suitable casing and cement conditions, the formation density calculated with the proposed method in cased borehole is in good agreement with the corresponding open-hole density.
{"title":"A NOVEL METHOD FOR FORMATION DENSITY MEASUREMENT IN CASED WELLS","authors":"Xinguang Wang, Dong Li, Lei Zhang, Feng Zhang, Wen-hao Wang, Huiping Gao, China Oilfield Services Limited, Xi 'an HuiNeng Electronic Equipment Co. Ltd","doi":"10.30632/spwla-2021-0065","DOIUrl":"https://doi.org/10.30632/spwla-2021-0065","url":null,"abstract":"Density logging is a fundamental logging method of open-hole logging series. In cased wells, the formation is usually treated as a cylindrical multiple-layer model including borehole, casing pipe, cement, and original formation, producing more complicated logging response compared to open-hole wells. Several studies have indicated that it is feasible to measure formation density using a density logging tool in cased well under certain conditions, of which the key problem is to determine casing thickness, cement thickness and cement density. This study proposes a novel method to evaluate formation density behind casing using a three-detector density tool. Considering that the backscattered gamma is easily affected by the density behind the casing, especially when the casing thickness is small, a designed ratio of high and low energy window counts of the scattered gamma spectrum is used to calculate casing thickness, which improves the lower limit of the detection. After obtaining casing thickness, the cylindrical multiple-layer model of cased well can be simplified to a cylindrical three-layer model, consisting of cased borehole, cement, and the original formation. Subsequently, the analytical expressions of the thickness of the middle layer (cement) as well as the density of the outer layer (original formation) can be derived based on the logging geometric factor concept, G, which borrowing from electric logging. Consequently, the cement thickness and original formation density could be calculated independently. To demonstrate the feasibility of the proposed method, experimental data are measured in a group of calibration wells. The data processing results show that the proposed analytical model fit well with the experimental data. In addition, the application conditions of the novel method are discussed based on experimental data. Finally, several log examples illustrate that under suitable casing and cement conditions, the formation density calculated with the proposed method in cased borehole is in good agreement with the corresponding open-hole density.","PeriodicalId":153712,"journal":{"name":"SPWLA 62nd Annual Online Symposium Transactions","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124785833","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 : 2021-05-17DOI: 10.30632/SPWLA-2021-0115
Feng Zhang, Qiu Fei, Q. Fang, Xiaoyang Zhang, Hui Zhang, F. Tang, Fan Jilin
Unconventional reservoirs have low porosity and complex mineral composition containing quartz, feldspar, calcite, dolomite, pyrite and kerogen, which may seriously reduce the accuracy of the porosity measurement. The multi-detector pulsed neutron logging technique was already used for determining porosity through the combination of inelastic and capture gamma ray information in different spacing. In this paper, the new parameter, which is characterized by thermal neutron count ratio and lithology factor based on element content, is proposed to determine porosity from the three-detector pulsed neutron element logging in unconventional reservoir. To evaluate mineral composition, lithology, and gas/oil/water saturation in unconventional reservoir, a new multi-detector pulsed neutron logging tool was put out. The instrument consists of two He-3 thermal neutron detectors and a LaBr3 gamma detector. Therefore, the combination of thermal neutron count ratio between near detector and long detector with lithology factor of element content can measure neutron porosity and eliminate the influence of complex lithology. Based on some calibration pit data measured in laboratory, as well as the numerical simulation method, the influences of different lithological characters and mineral types on the neutron count ratio were studied. Meanwhile, large numbers of stratigraphic models with different lithological characters and different mineral compositions were established using Monte Carlo simulation method, and the content of silicon, calcium, hydrogen, oxygen, magnesium, aluminum and iron under different stratigraphic conditions was determined by the spectral element solution. A regression analysis was conducted to establish the relationship between the content of elements and the lithologic factor. The count ratio difference stemming from different lithological and mineral compositions was eliminated through a combination of lithological correction factor and thermal neutron count ratio. Different mineral compositions of stratigraphic simulation models were set up for verification. The absolute error of porosity measurement was less than 1.0p.u. in the formations with porosity less than 15p.u., which verified the accuracy of this method for neutron porosity evaluation in complex lithological characters formations. Two field examples were processed by this new parameter which in combination of thermal neutron count ratio and formation elements content information from the three-detector pulsed neutron instrument, which indicated a good accuracy for unconventional oil and gas reservoir evaluation.
{"title":"AN ACCURATELY DETERMINING POROSITY METHOD FROM PULSED-NEUTRON ELEMENT LOGGING IN UNCONVENTIONAL RESERVOIRS","authors":"Feng Zhang, Qiu Fei, Q. Fang, Xiaoyang Zhang, Hui Zhang, F. Tang, Fan Jilin","doi":"10.30632/SPWLA-2021-0115","DOIUrl":"https://doi.org/10.30632/SPWLA-2021-0115","url":null,"abstract":"Unconventional reservoirs have low porosity and complex mineral composition containing quartz, feldspar, calcite, dolomite, pyrite and kerogen, which may seriously reduce the accuracy of the porosity measurement. The multi-detector pulsed neutron logging technique was already used for determining porosity through the combination of inelastic and capture gamma ray information in different spacing. In this paper, the new parameter, which is characterized by thermal neutron count ratio and lithology factor based on element content, is proposed to determine porosity from the three-detector pulsed neutron element logging in unconventional reservoir. To evaluate mineral composition, lithology, and gas/oil/water saturation in unconventional reservoir, a new multi-detector pulsed neutron logging tool was put out. The instrument consists of two He-3 thermal neutron detectors and a LaBr3 gamma detector. Therefore, the combination of thermal neutron count ratio between near detector and long detector with lithology factor of element content can measure neutron porosity and eliminate the influence of complex lithology. Based on some calibration pit data measured in laboratory, as well as the numerical simulation method, the influences of different lithological characters and mineral types on the neutron count ratio were studied. Meanwhile, large numbers of stratigraphic models with different lithological characters and different mineral compositions were established using Monte Carlo simulation method, and the content of silicon, calcium, hydrogen, oxygen, magnesium, aluminum and iron under different stratigraphic conditions was determined by the spectral element solution. A regression analysis was conducted to establish the relationship between the content of elements and the lithologic factor. The count ratio difference stemming from different lithological and mineral compositions was eliminated through a combination of lithological correction factor and thermal neutron count ratio. Different mineral compositions of stratigraphic simulation models were set up for verification. The absolute error of porosity measurement was less than 1.0p.u. in the formations with porosity less than 15p.u., which verified the accuracy of this method for neutron porosity evaluation in complex lithological characters formations. Two field examples were processed by this new parameter which in combination of thermal neutron count ratio and formation elements content information from the three-detector pulsed neutron instrument, which indicated a good accuracy for unconventional oil and gas reservoir evaluation.","PeriodicalId":153712,"journal":{"name":"SPWLA 62nd Annual Online Symposium Transactions","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130668366","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 : 2021-05-17DOI: 10.30632/spwla-2021-0080
Yong-hua Chen, Schlumberger, R. Bloemenkamp, Peter Schlicht, Lin Liang, L. Comparon
A new 2 1/8-in. outer-diameter photorealistic imager for oil-based muds (OBM) has recently started field testing in unconventional formations in North America. To obtain the best interpretation of its measurements, a two-step quantitative inversion workflow has been developed with a performance similar to the existing inversion workflows for the regular high-definition OBM imagers. The new inversion workflow provides borehole resistivity images, borehole rugosity images, and borehole dielectric permittivity images as well as multiple quality curves. The modeling of the new borehole imager is performed with a 2D axisymmetric finite element code. An efficient forward model is developed by fitting the tool response tables into fourth-order polynomials in terms of the sensor standoff, formation, and mud impedivities for broad ranges of model parameters. The fast forward model based on the polynomial fitting is calibrated against the actual tool measurements in a laboratory setup and applied in the inversion algorithms. The inversion workflow is tested with synthetic data and the inverted model parameters are compared with their true values to study and analyze their corresponding measurement sensitivity and optimize the inversion input parameters. It is used to invert several field test datasets in unconventional wells. The results show that the inversion results provide critical added value for formation evaluation, showing geological features that would otherwise be missed, such as fracture properties. Projection-based formation impedivity images, as available for the regular high-definition OBM imagers, are ideal for conductive formations but suffer from a rollover effect in resistive formations. In comparison, the image formed from the inverted formation resistivity does not roll over and is more consistent for resistive formations. The image formed by the inverted standoff reflects surface conditions of the borehole and can be used to interpret whether the fractures and the faults are open, closed, or damaged in the drilling process. Multiple image examples are given from unconventional wells to demonstrate that the inverted standoff image can reveal fractures when there is insufficient or even no contrast in medium properties. The inverted standoff image also serves as a diagnostic tool for interpreting borehole and tool conditions during the measurements. The inverted permittivity may have a larger dynamic range than the resistivity especially for unconventional formations, thus providing an alternative and potentially clearer borehole image.
{"title":"INVERSION-BASED MEASUREMENT INTERPRETATION OF A NEW THROUGH-THE-BIT OBM PHOTOREALISTIC BOREHOLE IMAGER","authors":"Yong-hua Chen, Schlumberger, R. Bloemenkamp, Peter Schlicht, Lin Liang, L. Comparon","doi":"10.30632/spwla-2021-0080","DOIUrl":"https://doi.org/10.30632/spwla-2021-0080","url":null,"abstract":"A new 2 1/8-in. outer-diameter photorealistic imager for oil-based muds (OBM) has recently started field testing in unconventional formations in North America. To obtain the best interpretation of its measurements, a two-step quantitative inversion workflow has been developed with a performance similar to the existing inversion workflows for the regular high-definition OBM imagers. The new inversion workflow provides borehole resistivity images, borehole rugosity images, and borehole dielectric permittivity images as well as multiple quality curves. The modeling of the new borehole imager is performed with a 2D axisymmetric finite element code. An efficient forward model is developed by fitting the tool response tables into fourth-order polynomials in terms of the sensor standoff, formation, and mud impedivities for broad ranges of model parameters. The fast forward model based on the polynomial fitting is calibrated against the actual tool measurements in a laboratory setup and applied in the inversion algorithms. The inversion workflow is tested with synthetic data and the inverted model parameters are compared with their true values to study and analyze their corresponding measurement sensitivity and optimize the inversion input parameters. It is used to invert several field test datasets in unconventional wells. The results show that the inversion results provide critical added value for formation evaluation, showing geological features that would otherwise be missed, such as fracture properties. Projection-based formation impedivity images, as available for the regular high-definition OBM imagers, are ideal for conductive formations but suffer from a rollover effect in resistive formations. In comparison, the image formed from the inverted formation resistivity does not roll over and is more consistent for resistive formations. The image formed by the inverted standoff reflects surface conditions of the borehole and can be used to interpret whether the fractures and the faults are open, closed, or damaged in the drilling process. Multiple image examples are given from unconventional wells to demonstrate that the inverted standoff image can reveal fractures when there is insufficient or even no contrast in medium properties. The inverted standoff image also serves as a diagnostic tool for interpreting borehole and tool conditions during the measurements. The inverted permittivity may have a larger dynamic range than the resistivity especially for unconventional formations, thus providing an alternative and potentially clearer borehole image.","PeriodicalId":153712,"journal":{"name":"SPWLA 62nd Annual Online Symposium Transactions","volume":"27 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130927918","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 : 2021-05-17DOI: 10.30632/SPWLA-2021-0119
G. Wang, D. Homan, D. Maggs, David G. Allen
It is well established that phase shift and attenuation measurements acquired by an electromagnetic propagation tool come with different depths of investigation (DOI). The attenuation measurement sees deeper into the formation than the phase shift measurement. This difference has been reported not only for the 2 MHz propagation resistivity tool, but also for the deep propagation tool that operates at 25 MHz. Although the difference has been demonstrated with modeling, test tank experiments and logs, a complete physical explanation has been notably absent since the introduction of the MHz-frequency propagation logging in 1980s. The question is so intriguing that it has been raised repeatedly over the past decades: what drives the difference of DOI for the two measurements that are acquired with the same electromagnetic field? In this paper, we revisit this problem with an aim of providing a physical insight to bridge the gap between theory and application. This is an extension of our recent work on the theory of apparent conductivity for propagation measurements. We address the problem by applying high-order geometric theory for low-frequency electromagnetic problems in lossy media in conjunction with the Taylor series expansion for the voltage ratio measured by a propagation tool. In so doing, we find that in a resistive formation where the dielectric effect is small: 1) the phase shift measurement is primarily due to the first-order eddy current induced in the formation; 2) in contrast, the leading source of the attenuation measurement is the second-order eddy current. Since the second-order eddy current is more spread out than the first-order eddy current, this explains why the DOI of attenuation resistivity is larger than that of phase shift resistivity. The difference in spatial distribution of two eddy currents is also the reason for the difference of vertical resolution between the two. The same root cause for the difference of DOI and vertical resolution also holds when comparing R-signal and X-signal from induction resistivity logging. Other properties shared by propagation and induction resistivity logging will be discussed, such as skin effect and dielectric effect, as well as their asymptotic properties in high-resistivity formations. We conclude that propagation and induction resistivity logging are essentially similar, even though the two measurement principles may seem rather different.
{"title":"A NEW LOOK AT THE DUAL DEPTH OF INVESTIGATION OF LWD PROPAGATION RESISTIVITY LOGGING","authors":"G. Wang, D. Homan, D. Maggs, David G. Allen","doi":"10.30632/SPWLA-2021-0119","DOIUrl":"https://doi.org/10.30632/SPWLA-2021-0119","url":null,"abstract":"It is well established that phase shift and attenuation measurements acquired by an electromagnetic propagation tool come with different depths of investigation (DOI). The attenuation measurement sees deeper into the formation than the phase shift measurement. This difference has been reported not only for the 2 MHz propagation resistivity tool, but also for the deep propagation tool that operates at 25 MHz. Although the difference has been demonstrated with modeling, test tank experiments and logs, a complete physical explanation has been notably absent since the introduction of the MHz-frequency propagation logging in 1980s. The question is so intriguing that it has been raised repeatedly over the past decades: what drives the difference of DOI for the two measurements that are acquired with the same electromagnetic field? In this paper, we revisit this problem with an aim of providing a physical insight to bridge the gap between theory and application. This is an extension of our recent work on the theory of apparent conductivity for propagation measurements. We address the problem by applying high-order geometric theory for low-frequency electromagnetic problems in lossy media in conjunction with the Taylor series expansion for the voltage ratio measured by a propagation tool. In so doing, we find that in a resistive formation where the dielectric effect is small: 1) the phase shift measurement is primarily due to the first-order eddy current induced in the formation; 2) in contrast, the leading source of the attenuation measurement is the second-order eddy current. Since the second-order eddy current is more spread out than the first-order eddy current, this explains why the DOI of attenuation resistivity is larger than that of phase shift resistivity. The difference in spatial distribution of two eddy currents is also the reason for the difference of vertical resolution between the two. The same root cause for the difference of DOI and vertical resolution also holds when comparing R-signal and X-signal from induction resistivity logging. Other properties shared by propagation and induction resistivity logging will be discussed, such as skin effect and dielectric effect, as well as their asymptotic properties in high-resistivity formations. We conclude that propagation and induction resistivity logging are essentially similar, even though the two measurement principles may seem rather different.","PeriodicalId":153712,"journal":{"name":"SPWLA 62nd Annual Online Symposium Transactions","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115361996","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 : 2021-05-17DOI: 10.30632/SPWLA-2021-0069
P. Craddock, Prakhar Srivastava, H. Datir, D. Rose, T. Zhou, L. Mosse, Lalitha Venkataramanan
This paper describes an innovative machine learning application, based on variational autoencoder frameworks, to quantify the concentrations and associated uncertainties of common minerals in sedimentary formations using the measurement of atomic element concentrations from geochemical spectroscopy logs as inputs. The algorithm comprises an input(s), encoder, decoder, output(s), and a novel cost function to optimize the model coefficients during training. The input to the algorithm is a set of dry-weight concentrations of atomic elements with their associated uncertainty. The first output is a set of dry-weight fractions of fourteen minerals, and the second output is a set of reconstructed dry-weight concentrations of the original elements. Both sets of outputs include estimates of uncertainty on their predictions. The encoder and decoder are multilayer feed-forward artificial neural networks (ANN), with their coefficients (weights) optimized during calibration (training). The cost function simultaneously minimizes error (the accuracy metric) and variance (the precision or robustness metric) on the mineral and reconstructed elemental outputs. Training of the weights is done using a set of several-thousand core samples with independent, high-fidelity elemental and mineral (quartz, potassium-feldspar, plagioclase-feldspar, illite, smectite, kaolinite, chlorite, mica, calcite, dolomite, ankerite, siderite, pyrite, and anhydrite) data. The algorithm provides notable advantages over existing methods to estimate formation lithology or mineralogy relying on simple linear, empirical, or nearest-neighbor functions. The ANN numerically capture the multi-dimensional and nonlinear geochemical relationship (mapping) between elements and minerals that is insufficiently described by prior methods. Training is iterative via backpropagation and samples from Gaussian distributions on each of the elemental inputs, rather than single values, for every sample at each iteration (epoch). These Gaussian distributions are chosen to specifically represent the unique statistical uncertainty of the dry-weight elements in the logging measurements. Sampling from Gaussian distributions during training reduces the potential for overfitting, provides robustness for log interpretations, and further enables a calibrated estimate of uncertainty on the mineral and reconstructed elemental outputs, all of which are lacking in prior methods. The framework of the algorithm is purposefully generalizable that it can be adapted across geochemical spectroscopy tools. The algorithm reasonably approximates a ‘global-average’ model that requires neither different calibrations nor expert parameterization or intervention for interpreting common oilfield sedimentary formations, although the framework is again purposefully generalizable so it can be optimized for local environments where desirable. The paper showcases field application of the method for estimating mineral type and abundance in oil
{"title":"ENHANCED MINERAL QUANTIFICATION AND UNCERTAINTY ANALYSIS FROM DOWNHOLE SPECTROSCOPY LOGS USING VARIATIONAL AUTOENCODERS","authors":"P. Craddock, Prakhar Srivastava, H. Datir, D. Rose, T. Zhou, L. Mosse, Lalitha Venkataramanan","doi":"10.30632/SPWLA-2021-0069","DOIUrl":"https://doi.org/10.30632/SPWLA-2021-0069","url":null,"abstract":"This paper describes an innovative machine learning application, based on variational autoencoder frameworks, to quantify the concentrations and associated uncertainties of common minerals in sedimentary formations using the measurement of atomic element concentrations from geochemical spectroscopy logs as inputs. The algorithm comprises an input(s), encoder, decoder, output(s), and a novel cost function to optimize the model coefficients during training. The input to the algorithm is a set of dry-weight concentrations of atomic elements with their associated uncertainty. The first output is a set of dry-weight fractions of fourteen minerals, and the second output is a set of reconstructed dry-weight concentrations of the original elements. Both sets of outputs include estimates of uncertainty on their predictions. The encoder and decoder are multilayer feed-forward artificial neural networks (ANN), with their coefficients (weights) optimized during calibration (training). The cost function simultaneously minimizes error (the accuracy metric) and variance (the precision or robustness metric) on the mineral and reconstructed elemental outputs. Training of the weights is done using a set of several-thousand core samples with independent, high-fidelity elemental and mineral (quartz, potassium-feldspar, plagioclase-feldspar, illite, smectite, kaolinite, chlorite, mica, calcite, dolomite, ankerite, siderite, pyrite, and anhydrite) data. The algorithm provides notable advantages over existing methods to estimate formation lithology or mineralogy relying on simple linear, empirical, or nearest-neighbor functions. The ANN numerically capture the multi-dimensional and nonlinear geochemical relationship (mapping) between elements and minerals that is insufficiently described by prior methods. Training is iterative via backpropagation and samples from Gaussian distributions on each of the elemental inputs, rather than single values, for every sample at each iteration (epoch). These Gaussian distributions are chosen to specifically represent the unique statistical uncertainty of the dry-weight elements in the logging measurements. Sampling from Gaussian distributions during training reduces the potential for overfitting, provides robustness for log interpretations, and further enables a calibrated estimate of uncertainty on the mineral and reconstructed elemental outputs, all of which are lacking in prior methods. The framework of the algorithm is purposefully generalizable that it can be adapted across geochemical spectroscopy tools. The algorithm reasonably approximates a ‘global-average’ model that requires neither different calibrations nor expert parameterization or intervention for interpreting common oilfield sedimentary formations, although the framework is again purposefully generalizable so it can be optimized for local environments where desirable. The paper showcases field application of the method for estimating mineral type and abundance in oil","PeriodicalId":153712,"journal":{"name":"SPWLA 62nd Annual Online Symposium Transactions","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125972028","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 : 2021-05-17DOI: 10.30632/spwla-2021-0058
Daria Olszowska, Gabriel Gallardo-Giozza, C. Torres‐Verdín
Porous rocks are rarely homogeneous. Significant spatial variations in elastic properties are often observed in rocks due to depositional, diagenetic, and structural processes. In laminated sandstones, complex carbonates, or unconventional formations, elastic properties can vary on scales from millimeters to tens of meters. Detection of inhomogeneities and their size in rocks is crucial for fracture propagation design, height containment assessment, and for improving well/reservoir productivity. Most laboratory techniques used to measure rock elastic properties fail to distinguish mid-scale anisotropy; results are subject to spatial averaging effects. We introduce a new experimental method to measure continuous compressional- and shear-wave logs of core samples based on measurements of angle-dependent ultrasonic reflection coefficients. Simultaneously with reflected waves, we detect and interpret refracted waves as an independent way to estimate acoustic wave velocities to support the analysis. Our laboratory system is equipped with an array of receivers to continuously collect measurements. At each core location, we acquire acoustic waveforms at multiple transmitter-receiver angles using a pitch-catch acquisition mode (similar to standard sonic tools). This acquisition mode uses multiple receivers, allowing us to obtain measurements at different incidence angles without moving the sample and keeping the distance traveled by reflected waves constant, thereby eliminating the need for geometrical spreading corrections in reflection-coefficient calculations. Reflectivity-vs.-angle measurements are then matched with numerical simulations to estimate rock elastic properties. Ultrasonic reflection-coefficient measurements are successfully used to estimate dynamic elastic rock properties of homogeneous and layered rock samples. For homogenous samples, values are within a 5% range when compared to those obtained with the standard acoustic transmission method. Measurements acquired on natural and artificially constructed samples show significant departures from homogeneous behavior caused by layering. Laboratory reflection-coefficient measurements enable detection of inch-scale anisotropy within the rock, leading to improved assessment of formation elastic properties. Furthermore, continuous core measurements provide high-resolution reflection-coefficient information which is complementary to open-hole ultrasonic logs.
{"title":"ULTRASONIC ANGLE-DEPENDENT REFLECTIVITY IN COMPLEX ROCKS FOR IMPROVED INTERPRETATION OF SONIC AND ULTRASONIC LOGS","authors":"Daria Olszowska, Gabriel Gallardo-Giozza, C. Torres‐Verdín","doi":"10.30632/spwla-2021-0058","DOIUrl":"https://doi.org/10.30632/spwla-2021-0058","url":null,"abstract":"Porous rocks are rarely homogeneous. Significant spatial variations in elastic properties are often observed in rocks due to depositional, diagenetic, and structural processes. In laminated sandstones, complex carbonates, or unconventional formations, elastic properties can vary on scales from millimeters to tens of meters. Detection of inhomogeneities and their size in rocks is crucial for fracture propagation design, height containment assessment, and for improving well/reservoir productivity. Most laboratory techniques used to measure rock elastic properties fail to distinguish mid-scale anisotropy; results are subject to spatial averaging effects. We introduce a new experimental method to measure continuous compressional- and shear-wave logs of core samples based on measurements of angle-dependent ultrasonic reflection coefficients. Simultaneously with reflected waves, we detect and interpret refracted waves as an independent way to estimate acoustic wave velocities to support the analysis. Our laboratory system is equipped with an array of receivers to continuously collect measurements. At each core location, we acquire acoustic waveforms at multiple transmitter-receiver angles using a pitch-catch acquisition mode (similar to standard sonic tools). This acquisition mode uses multiple receivers, allowing us to obtain measurements at different incidence angles without moving the sample and keeping the distance traveled by reflected waves constant, thereby eliminating the need for geometrical spreading corrections in reflection-coefficient calculations. Reflectivity-vs.-angle measurements are then matched with numerical simulations to estimate rock elastic properties. Ultrasonic reflection-coefficient measurements are successfully used to estimate dynamic elastic rock properties of homogeneous and layered rock samples. For homogenous samples, values are within a 5% range when compared to those obtained with the standard acoustic transmission method. Measurements acquired on natural and artificially constructed samples show significant departures from homogeneous behavior caused by layering. Laboratory reflection-coefficient measurements enable detection of inch-scale anisotropy within the rock, leading to improved assessment of formation elastic properties. Furthermore, continuous core measurements provide high-resolution reflection-coefficient information which is complementary to open-hole ultrasonic logs.","PeriodicalId":153712,"journal":{"name":"SPWLA 62nd Annual Online Symposium Transactions","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132223512","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 : 2021-05-17DOI: 10.30632/SPWLA-2021-0109
D. Hill, E. Crain
Potash minerals are a source of potassium, which is used for the manufacture of gunpowder and fertilizer. Commercial potash mineralization is often discovered when petroleum wells are drilled through evaporite sequences and the Gamma Ray log “goes off scale”. This is because potassium is one of the naturally occurring radioactive elements, emitting gamma rays from the 40K isotope, in its decay to 40Ar. However, not all potash minerals may be commercial sources of potassium via underground mechanical or solution mining techniques and Potassium is not the only radioactive element. For example, the mineralogy of the McNutt “Potash” member of the Salado Formation in SE New Mexico, is extremely complex, consisting of multiple thin (i.e., less than 10 ft thick) beds of six low-grade (radioactive) potash minerals, only two of which are commercial. There are also four non-radioactive evaporite minerals, one of which interferes with potash milling chemistry, and numerous claystones and Marker Beds (shales), with GR count rates comparable to the low-grade potash. Because of this complexity, traditional wireline and Logging While Drilling Potash Assay techniques, such as Gamma Ray log-to-core assay transforms, may not be sufficient to identify potentially commercial potash mineralization, for underground mining. Crain and Anderson (1966) and Hill (2019) developed linear programming, and multi-mineral analyses, respectively, to estimate Potash mineralogy and grades. However, both of these approaches require complete sets of multiple log measurements. In SE New Mexico, petroleum wells are drilled through the McNutt “Potash” member of the Salado Formation, with air, cased and drilled out to TD in the underlying sediments, with water based mud. Complete log suites are then run from TD to the casing shoe, with only the GR and neutron logs recorded through the cased evaporite sequence for stratigraphic and structural correlation. As a result, numerous oil and gas wells, in SE New Mexico, have cased hole gamma ray and neutron logs, through the Salado Evaporite. Logs, from these wells could provide a rapid Potash screening database, if used properly. A simple screening cross-plot technique, the Potash Identification (PID) plot, utilizing only Gamma Ray and Neutron Porosity, is proposed and successfully demonstrated, as a potential screening tool. This technique can be used with both open and cased-hole petroleum well logs, as well as core hole wire-line logs, and provides discrimination of commercial potash mineralization from non-commercial (potash and non-potash) radioactive mineralization. Case histories of the use of PID cross plots in the evaporite basins of Michigan, Nova Scotia, Saskatchewan, and SE New Mexico are described. The technique may also be useful in screening potential potash deposits in China, Europe, North Africa, and South America.
{"title":"RAPID CROSS-PLOT DISCRIMINATION OF COMMERCIAL POTASH MINERALIZATION – CASE HISTORIES","authors":"D. Hill, E. Crain","doi":"10.30632/SPWLA-2021-0109","DOIUrl":"https://doi.org/10.30632/SPWLA-2021-0109","url":null,"abstract":"Potash minerals are a source of potassium, which is used for the manufacture of gunpowder and fertilizer. Commercial potash mineralization is often discovered when petroleum wells are drilled through evaporite sequences and the Gamma Ray log “goes off scale”. This is because potassium is one of the naturally occurring radioactive elements, emitting gamma rays from the 40K isotope, in its decay to 40Ar. However, not all potash minerals may be commercial sources of potassium via underground mechanical or solution mining techniques and Potassium is not the only radioactive element. For example, the mineralogy of the McNutt “Potash” member of the Salado Formation in SE New Mexico, is extremely complex, consisting of multiple thin (i.e., less than 10 ft thick) beds of six low-grade (radioactive) potash minerals, only two of which are commercial. There are also four non-radioactive evaporite minerals, one of which interferes with potash milling chemistry, and numerous claystones and Marker Beds (shales), with GR count rates comparable to the low-grade potash. Because of this complexity, traditional wireline and Logging While Drilling Potash Assay techniques, such as Gamma Ray log-to-core assay transforms, may not be sufficient to identify potentially commercial potash mineralization, for underground mining. Crain and Anderson (1966) and Hill (2019) developed linear programming, and multi-mineral analyses, respectively, to estimate Potash mineralogy and grades. However, both of these approaches require complete sets of multiple log measurements. In SE New Mexico, petroleum wells are drilled through the McNutt “Potash” member of the Salado Formation, with air, cased and drilled out to TD in the underlying sediments, with water based mud. Complete log suites are then run from TD to the casing shoe, with only the GR and neutron logs recorded through the cased evaporite sequence for stratigraphic and structural correlation. As a result, numerous oil and gas wells, in SE New Mexico, have cased hole gamma ray and neutron logs, through the Salado Evaporite. Logs, from these wells could provide a rapid Potash screening database, if used properly. A simple screening cross-plot technique, the Potash Identification (PID) plot, utilizing only Gamma Ray and Neutron Porosity, is proposed and successfully demonstrated, as a potential screening tool. This technique can be used with both open and cased-hole petroleum well logs, as well as core hole wire-line logs, and provides discrimination of commercial potash mineralization from non-commercial (potash and non-potash) radioactive mineralization. Case histories of the use of PID cross plots in the evaporite basins of Michigan, Nova Scotia, Saskatchewan, and SE New Mexico are described. The technique may also be useful in screening potential potash deposits in China, Europe, North Africa, and South America.","PeriodicalId":153712,"journal":{"name":"SPWLA 62nd Annual Online Symposium Transactions","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130371682","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 : 2021-05-17DOI: 10.30632/SPWLA-2021-0114
A. Bertolini, V. Simoes, Marianna Dantas, P. Machado
The filtrate contamination cleanup time on a complex carbonate well using a traditional wireline formation tester (WFT) tool can vary from a couple of hours to over half a day. The method proposed aims at reducing operational time to collect a low-contamination formation fluid sample by determining regions with a smaller depth of invasion using a forward model simulation that considers static and dynamic formation properties to predict the radial profile of invasion. The mud filtrate invasion process was modeled considering the static and dynamic properties of the near-wellbore region in an industry reference reservoir simulator, and it integrates three mechanisms for fluid flow: Darcy’s law, material balance, and capillary pressure. The physical robustness of the reservoir simulator was united to a data-driven model to reduce the computational cost. This proxy model is based on a trained neural network with a broad range of scenarios to predict the numerical simulation results with high accuracy. The invasion estimation from the model is then used to predict the filtrate cleanup time using an industry consolidated numerical modeling. One of the variables influencing most of the cleanup time is the depth of mud filtrate invasion. Thus, reducing this time is a determinant for the WFT operational efficiency. The model for mud invasion has been successfully tested on a complex carbonate well, and the results for the depth of mud invasion were comparable to the results obtained with a commercial data-driven inversion using multiple resistivity channels. The estimated cleanup time using the results of depth of invasion predicted by the forward model has been compared and matched with real carbonate sampling stations, and there was a high correlation indicating that zones with lower depth of invasion required less cleanup time. Besides, using the history-matched cases, different WFT technologies such as single and radial probes, focused, unfocused, and dual-packer WFT inlets were evaluated, showing a high potential for reduction of operational time when properly planned and selected for the specific type of reservoir. The proposed methodology is a viable method for understanding the clean-up behavior in different reservoir scenarios using different WFT technologies. The innovation of this method relies on the data calibration using basic and advanced petrophysical properties through a data-driven model based on a trained neural network to reduce the uncertainty in the predicted invasion radial profile and the WFT cleanup time. The reliability on the theoretical results was increased using real data calibration, and this calibrated theoretical model has been used to guide the sampling depth selection, saving operational time.
{"title":"USING PROXY SIMULATOR FOR RESERVOIR ZONE SELECTION AND REDUCING THE FORMATION TESTER CLEANUP OPERATIONAL TIME","authors":"A. Bertolini, V. Simoes, Marianna Dantas, P. Machado","doi":"10.30632/SPWLA-2021-0114","DOIUrl":"https://doi.org/10.30632/SPWLA-2021-0114","url":null,"abstract":"The filtrate contamination cleanup time on a complex carbonate well using a traditional wireline formation tester (WFT) tool can vary from a couple of hours to over half a day. The method proposed aims at reducing operational time to collect a low-contamination formation fluid sample by determining regions with a smaller depth of invasion using a forward model simulation that considers static and dynamic formation properties to predict the radial profile of invasion. The mud filtrate invasion process was modeled considering the static and dynamic properties of the near-wellbore region in an industry reference reservoir simulator, and it integrates three mechanisms for fluid flow: Darcy’s law, material balance, and capillary pressure. The physical robustness of the reservoir simulator was united to a data-driven model to reduce the computational cost. This proxy model is based on a trained neural network with a broad range of scenarios to predict the numerical simulation results with high accuracy. The invasion estimation from the model is then used to predict the filtrate cleanup time using an industry consolidated numerical modeling. One of the variables influencing most of the cleanup time is the depth of mud filtrate invasion. Thus, reducing this time is a determinant for the WFT operational efficiency. The model for mud invasion has been successfully tested on a complex carbonate well, and the results for the depth of mud invasion were comparable to the results obtained with a commercial data-driven inversion using multiple resistivity channels. The estimated cleanup time using the results of depth of invasion predicted by the forward model has been compared and matched with real carbonate sampling stations, and there was a high correlation indicating that zones with lower depth of invasion required less cleanup time. Besides, using the history-matched cases, different WFT technologies such as single and radial probes, focused, unfocused, and dual-packer WFT inlets were evaluated, showing a high potential for reduction of operational time when properly planned and selected for the specific type of reservoir. The proposed methodology is a viable method for understanding the clean-up behavior in different reservoir scenarios using different WFT technologies. The innovation of this method relies on the data calibration using basic and advanced petrophysical properties through a data-driven model based on a trained neural network to reduce the uncertainty in the predicted invasion radial profile and the WFT cleanup time. The reliability on the theoretical results was increased using real data calibration, and this calibrated theoretical model has been used to guide the sampling depth selection, saving operational time.","PeriodicalId":153712,"journal":{"name":"SPWLA 62nd Annual Online Symposium Transactions","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117265886","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 : 2021-05-17DOI: 10.30632/SPWLA-2021-0033
Ping Zhang, Wael Abdallah, G. Wang, S. Ma
It is desirable to evaluate the possibility of developing a deeper dielectric permittivity based Sw measurement for various petrophysical applications. The low frequency, (< MHz), resistivity-based method for water saturation (Sw) evaluation is the desired method in the industry due to its deepest depth of investigation (DOI, up to 8 ft). However, the method suffers from higher uncertainty when formation water is very fresh or has mixed salinity. Dielectric permittivity and conductivity dispersion have been used to estimate Sw and salinity. The current dielectric dispersion tools, however, have very shallow DOI due to their high measurement frequency up to GHz, which most likely confines the measurements within the near wellbore mud-filtrate invaded zones. In this study, effective medium-model simulations were conducted to study different electromagnetic (EM) induced-polarization effects and their relationships to rock petrophysical properties. Special attention is placed on the complex conductivity at 2 MHz due to its availability in current logging tools. It is known that the complex dielectric saturation interpretation at the MHz range is quite difficult due to lack of fully understood of physics principles on complex dielectric responses, especially when only single frequency signal is used. Therefore, our study is focused on selected key parameters: water-filled porosity, salinity, and grain shape, and their effects on the modeled formation conductivity and permittivity. To simulate field logs, some of the petrophysical parameters mentioned above are generated randomly within expected ranges. Formation conductivity and permittivity are then calculated using our petrophysical model. The calculated results are then mixed with random noises of 10% to make them more realistic like downhole logs. The synthetic conductivity and permittivity logs are used as inputs in a neural network application to explore possible correlations with water-filled porosity. It is found that while the conductivity and permittivity logs are generated from randomly selected petrophysical parameters, they are highly correlated with water-filled porosity. Furthermore, if new conductivity and permittivity logs are generated with different petrophysical parameters, the correlations defined before can be used to predict water-filled porosity in the new datasets. We also found that for freshwater environments, the conductivity has much lower correlation with water-filled porosity than the one derived from the permittivity. However, the correlations are always improved when both conductivity and permittivity were used. This exercise serves as proof of concept, which opens an opportunity for field data applications. Field logs confirm the findings in the model simulations. Two propagation resistivity logs measured at 2 MHz are processed to calculate formation conductivity and permittivity. Using independently estimated water-filled porosity, a model was trained using a neural
{"title":"DEEP DIELECTRIC-BASED WATER SATURATION IN FRESHWATER AND MIXED SALINITY ENVIRONMENTS","authors":"Ping Zhang, Wael Abdallah, G. Wang, S. Ma","doi":"10.30632/SPWLA-2021-0033","DOIUrl":"https://doi.org/10.30632/SPWLA-2021-0033","url":null,"abstract":"It is desirable to evaluate the possibility of developing a deeper dielectric permittivity based Sw measurement for various petrophysical applications. The low frequency, (< MHz), resistivity-based method for water saturation (Sw) evaluation is the desired method in the industry due to its deepest depth of investigation (DOI, up to 8 ft). However, the method suffers from higher uncertainty when formation water is very fresh or has mixed salinity. Dielectric permittivity and conductivity dispersion have been used to estimate Sw and salinity. The current dielectric dispersion tools, however, have very shallow DOI due to their high measurement frequency up to GHz, which most likely confines the measurements within the near wellbore mud-filtrate invaded zones. In this study, effective medium-model simulations were conducted to study different electromagnetic (EM) induced-polarization effects and their relationships to rock petrophysical properties. Special attention is placed on the complex conductivity at 2 MHz due to its availability in current logging tools. It is known that the complex dielectric saturation interpretation at the MHz range is quite difficult due to lack of fully understood of physics principles on complex dielectric responses, especially when only single frequency signal is used. Therefore, our study is focused on selected key parameters: water-filled porosity, salinity, and grain shape, and their effects on the modeled formation conductivity and permittivity. To simulate field logs, some of the petrophysical parameters mentioned above are generated randomly within expected ranges. Formation conductivity and permittivity are then calculated using our petrophysical model. The calculated results are then mixed with random noises of 10% to make them more realistic like downhole logs. The synthetic conductivity and permittivity logs are used as inputs in a neural network application to explore possible correlations with water-filled porosity. It is found that while the conductivity and permittivity logs are generated from randomly selected petrophysical parameters, they are highly correlated with water-filled porosity. Furthermore, if new conductivity and permittivity logs are generated with different petrophysical parameters, the correlations defined before can be used to predict water-filled porosity in the new datasets. We also found that for freshwater environments, the conductivity has much lower correlation with water-filled porosity than the one derived from the permittivity. However, the correlations are always improved when both conductivity and permittivity were used. This exercise serves as proof of concept, which opens an opportunity for field data applications. Field logs confirm the findings in the model simulations. Two propagation resistivity logs measured at 2 MHz are processed to calculate formation conductivity and permittivity. Using independently estimated water-filled porosity, a model was trained using a neural ","PeriodicalId":153712,"journal":{"name":"SPWLA 62nd Annual Online Symposium Transactions","volume":"141 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123759490","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 : 2021-05-17DOI: 10.30632/SPWLA-2021-0086
Y. Askoul, G. Sibbald, A. Hooker, J. Banks, Total E P Uk Ltd
The necessity of knowing formation pressure is crucial to classifying pressure regimes for better understanding in well planning and to de-risk potential abnormal pressure conditions before any future field development wells are drilled, consequently minimizing operational cost. Wireline formation pressure testing has been a useful and reliable technology, that has evolved to confront the challenge of ultra-low permeable reservoir conditions by innovating and improving pump capability, accuracy in pressure measurements, automated control and the implantation of Formation Rate Analysis (FRA) intertwined with an Artificial Intelligent tool. In any pressure testing, the key factor is to be able to withdraw volume from the formation to generate a disturbance on formation pore pressure that a pressure gauge can measure. In the past this has been a difficult task in ultra-low permeable zones. The new generation of wireline tools are capable of withdrawing volume from ultra-low permeable reservoirs, with mobilities lower than 0.01mD/cP. This has been made possible by utilizing control of the pump speed down to 0.0003cc/s which then gives the operator the ability to test ultra-tight formations without the need for inflatable packers. By pulling down the pressure at an extremely low rate and using Artificial Intelligence to control the rate by knowing the formation rate, a proportional amount of volume can be extracted without calling it a tight test. During the operation by observing the rate, and making sure the pump is not oscillating, which indicates the formation rate is lower than the lowest rate the pump can withdraw, the test can be validated for formation flow and the pressure transient of the build – up can be analysed to confirm that at least spherical flow is observed. Once reservoir communication has been confirmed and by analysing drawdown and build-up pressure versus volume withdrawn and implementing the FRA equation, the reservoir pressure can be back calculated by considering isothermal compressibility and FRA slope. This paper highlights the best technical approach to quality check and quality control these tests, showing examples of various wells, where the technique has been used to predict a formation pressure, which can be used for further use for field development, drilling optimisation and production profiles. These pressures would never have been possible using static rates and volume.
{"title":"FORMATION PRESSURE ESTIMATION IN ULTRA-LOW PERMEABLE RESERVOIRS EMPLOYING FORMATION RATE ANALYSIS (FRA) AND ARTIFICIAL INTELLIGENCE CONTROLLED TOOLS","authors":"Y. Askoul, G. Sibbald, A. Hooker, J. Banks, Total E P Uk Ltd","doi":"10.30632/SPWLA-2021-0086","DOIUrl":"https://doi.org/10.30632/SPWLA-2021-0086","url":null,"abstract":"The necessity of knowing formation pressure is crucial to classifying pressure regimes for better understanding in well planning and to de-risk potential abnormal pressure conditions before any future field development wells are drilled, consequently minimizing operational cost. Wireline formation pressure testing has been a useful and reliable technology, that has evolved to confront the challenge of ultra-low permeable reservoir conditions by innovating and improving pump capability, accuracy in pressure measurements, automated control and the implantation of Formation Rate Analysis (FRA) intertwined with an Artificial Intelligent tool. In any pressure testing, the key factor is to be able to withdraw volume from the formation to generate a disturbance on formation pore pressure that a pressure gauge can measure. In the past this has been a difficult task in ultra-low permeable zones. The new generation of wireline tools are capable of withdrawing volume from ultra-low permeable reservoirs, with mobilities lower than 0.01mD/cP. This has been made possible by utilizing control of the pump speed down to 0.0003cc/s which then gives the operator the ability to test ultra-tight formations without the need for inflatable packers. By pulling down the pressure at an extremely low rate and using Artificial Intelligence to control the rate by knowing the formation rate, a proportional amount of volume can be extracted without calling it a tight test. During the operation by observing the rate, and making sure the pump is not oscillating, which indicates the formation rate is lower than the lowest rate the pump can withdraw, the test can be validated for formation flow and the pressure transient of the build – up can be analysed to confirm that at least spherical flow is observed. Once reservoir communication has been confirmed and by analysing drawdown and build-up pressure versus volume withdrawn and implementing the FRA equation, the reservoir pressure can be back calculated by considering isothermal compressibility and FRA slope. This paper highlights the best technical approach to quality check and quality control these tests, showing examples of various wells, where the technique has been used to predict a formation pressure, which can be used for further use for field development, drilling optimisation and production profiles. These pressures would never have been possible using static rates and volume.","PeriodicalId":153712,"journal":{"name":"SPWLA 62nd Annual Online Symposium Transactions","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131535044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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