Petrophysics – The SPWLA Journal of Formation Evaluation and Reservoir Description最新文献

{"title":"A New Workflow for Estimating Reservoir Properties With Gradient Boosting Model and Joint Inversion Using MWD Measurements","authors":"Hyungjoo Lee, Alexander M. Mitkus, Andrew Pare, Kenneth McCarthy, Marc Willerth, Paul Reynerson, Tannor Ziehm, Timothy Gee","doi":"10.30632/pjv65n2-2024a5","DOIUrl":"https://doi.org/10.30632/pjv65n2-2024a5","url":null,"abstract":"Triple-combo logs are important measurements for estimating geological, petrophysical, and geomechanical properties. Unfortunately, wireline and advanced logging-while-drilling (LWD) logs are typically dropped from the formation evaluation plan for unconventional wells due to economic constraints or borehole instability risks. Available measurements are typically measurement-while-drilling (MWD) gamma ray (GR) logs, along with surface measurements such as weight on bit (WOB), rate of penetration (ROP), torque, rotation per minute (RPM), and differential pressure. The development of a robust and rapid model for predicting reservoir properties using this limited data set would be of high value for geological evaluation. Estimating such properties is a challenging task due to the nonlinear relationship between the available log data and unknown reservoir properties. A novel workflow that combines two sequential models is presented. First is a machine-learning (ML) algorithm to predict triple-combo logs from drilling dynamics and GR logs. To train the ML algorithm, well logs obtained from multiple wells located in the Eagle Ford and Permian Basins are scrutinized to identify important features. This process includes depth shifting, outlier detection, and feature selection, which allows for strategic hyperparameter tuning. Several regression algorithms are investigated, and it is found that gradient boosting algorithms yield superior prediction performance. Unlike random forest methods, boosting algorithms train predictors sequentially, each trying to correct its predecessor. After triple-combo logs are predicted from MWD logs, a physics-based joint inversion model is applied to estimate various reservoir properties. The trained model is deployed on a blind test well, and the predicted logs show excellent agreement compared to the corresponding triple-combo measurements. The multimineral inversion using predicted triple-combo logs yields a geologic model that is validated with elemental capture spectroscopy (ECS) measurements. Additionally, reconstructed logs from the forward model closely match measured logs by minimizing the cost function. Therefore, real-time estimated geological, petrophysical, and geomechanical properties can reveal complex geologic information and be used to mitigate uncertainty related to drilling optimization, reservoir characterization, development planning, and reserve estimation. Using the MWD logs to predict triple-combo logs followed by a joint inversion is an innovative approach for geological evaluation with a limited data set. The developed workflow can successfully provide (1) geologic lithofacies identification and rock typing, (2) more confidence in real-time drilling operation, (3) reservoir properties prediction, (4) missing log imputations and pseudo-log generation with forward modeling, (5) guidance for future logging and perforation, (6) reference for seismic quantitative interpretation (QI) and well tie, and (","PeriodicalId":170688,"journal":{"name":"Petrophysics – The SPWLA Journal of Formation Evaluation and Reservoir Description","volume":"504 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140773492","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Study on Electrical Characteristics and Formation Mechanism of Micro-Ion Capacitor in Shale Pore and Fracture Structure","authors":"Hongqi Liu, Haibo Liao, Zhanshan Xiao, Shanjun Li, Liquan Ran, Dong Chen","doi":"10.30632/pjv65n2-2024a2","DOIUrl":"https://doi.org/10.30632/pjv65n2-2024a2","url":null,"abstract":"Due to the micro/nanoscale and intricate pore structure, poor connectivity, complex pathways, the presence of microfractures, and the coexistence of organic and inorganic pores, shale and other tight reservoirs exhibit increasingly complex conductive characteristics. This paper mainly studied the electrical properties of shale based on experimental test data, including scanning electron microscope (SEM) thin-section and microtomography CT (μ-CT) images, and analyzed the shale pore type, pore structure characteristics, and development of fracture. Then, the distribution of pyrite, content, and graphitization of organics and their influence on the electrical properties are discussed. Furthermore, the double electrical layer and zeta potential in the shale zone were discussed in depth. The results revealed that, within the content of pyrite, organics, and its graphitization, the vitrinite maturity are inversely proportional to shale resistivity. It was also found that in the presence of an external electromagnetic field, the fluid in shale pores is subjected to the combined strength of pore pressure and external field potential difference. Thus, its response equation should be an improved Navier-Stokes equation, which considers pore pressure, zeta potential, and Coulomb force. When shale is subjected to an external electromagnetic field, due to the complex pores structure and organic and inorganic minerals, it will represent more of a dielectric-like property than electricity. So, it will form special microscopic ionic capacitors, which are different from common plate capacitors. There are three special kinds of microscopic ionic capacitors, they are (I) the intergranular pore microscopic ionic capacitor model, (II) the particle with isolated pore microscopic ionic capacitor model, and (III) the pyrite or graphite or other organics microscopic ionic capacitor model. Finally, the characteristics of microscopic ion capacitors are summarized: irregular polar area and varying distance between poles, varying charges with time, and salinity of the formation water.","PeriodicalId":170688,"journal":{"name":"Petrophysics – The SPWLA Journal of Formation Evaluation and Reservoir Description","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140765945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Core Analysis Using Nuclear Magnetic Resonance","authors":"Yan Zhang, Yiqiao Song, Sihui Luo, Tingting Lin, Huabing Liu","doi":"10.30632/pjv65n2-2024a3","DOIUrl":"https://doi.org/10.30632/pjv65n2-2024a3","url":null,"abstract":"Core analysis is critical for oil and gas exploration and recovery. Nuclear magnetic resonance (NMR) has been widely applied to the petroleum industry for many years, and NMR core analysis plays an important role in supporting borehole NMR formation evaluation and understanding the mechanisms of petrophysics and petrochemistry. It’s unfortunate, however, that there has been a lack of commented descriptions of the basic procedures for NMR rock core analysis in the literature, which has led to issues of comparability and repeatability of NMR measurements between different laboratories. In this paper, we present a brief guideline for NMR rock core analysis of conventional T2, T1, T1-T2, and D-T2 measurements. As an established procedure in daily laboratory work, NMR core analysis includes three sophisticated steps: rock sample preparation, an NMR experiment, and data analysis. The acquisition and saturation of rock samples are described, and corresponding solutions are also considered. Detailed NMR experimental measurements, data setting, and calibration are addressed. Laplace inversion for different NMR experiments and models for estimation of porosity, irreducible water, permeability, pore structure, and oil saturation are included. The aim of this paper is to try to standardize general NMR experiments for rock core analysis.","PeriodicalId":170688,"journal":{"name":"Petrophysics – The SPWLA Journal of Formation Evaluation and Reservoir Description","volume":"23 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140765989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experimental Research on the Permeability of Granite Under Different Temperature Cycles","authors":"Li Yu, Haonan Li, Yue Wu, Weihao Wang, Xinyuan Zhang, Yongchuan Zhao","doi":"10.30632/pjv65n1-2024a5","DOIUrl":"https://doi.org/10.30632/pjv65n1-2024a5","url":null,"abstract":"In this paper, through the permeability test of granite under different temperature cycles, the change law of porosity and permeability of rock samples after different temperature cycles was studied, and the relationship between the P-wave velocity and porosity and permeability was established by regression analysis. The results show that the porosity and permeability of the granite samples decreased significantly in one to three high-temperature cycles, showing a logarithmic change, and with the increase of the number of cycles, the decreasing rate gradually decreased after five to 10 thermal cycles, which is beneficial to the long-term development of deep geothermal resources. Under thermal cycles at different temperatures, the P-wave velocity of granite has a logarithmic correlation with permeability and porosity. As the number of cycles increases, the relationship between permeability, porosity, and P-wave velocity changes from a logarithmic relationship between one to three cycles to a linear relationship between five to 10 cycles. After thermal cycle treatment at different temperatures, there is an excellent logarithmic relationship between the P-wave velocity and porosity and permeability, and it has a high correlation. The porosity and permeability of granite can be estimated nondestructively by measuring the wave velocity. Using a scanning electron microscope (SEM) to observe the granite at 450℃, trivial particles appeared between the pore structure, and the internal structure of the rock sample was destroyed under the action of the thermal cycle. The change mechanism of physical property deterioration in deep geothermal energy mining is revealed, guiding deep geothermal energy mining.","PeriodicalId":170688,"journal":{"name":"Petrophysics – The SPWLA Journal of Formation Evaluation and Reservoir Description","volume":"108 5-6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139880067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Well-Log-Based Reservoir Property Estimation With Machine Learning: A Contest Summary","authors":"Lei Fu, Yanxiang Yu, Chicheng Xu, Michael Ashby, Andrew McDonald, Wen Pan, Tianqi Deng, István Szabó, Pál P. Hanzelik, Csilla Kalmár, Saleh Alatwah, Jaehyuk Lee","doi":"10.30632/pjv65n1-2024a6","DOIUrl":"https://doi.org/10.30632/pjv65n1-2024a6","url":null,"abstract":"Well logs are processed and interpreted to estimate in-situ reservoir properties, which are essential for reservoir modeling, reserve estimation, and production forecasting. While the traditional methods are mostly based on multimineral physics or empirical formulae, machine learning provides an alternative data-driven approach that requires much less a-priori geological or petrophysical information. From October 2021 to March 2022, the Petrophysical Data-Driven Analytics Special Interest Group (PDDA SIG) of the Society of Petrophysicists and Well Log Analysts (SPWLA) hosted a machine-learning contest aiming to develop data-driven models for estimating reservoir properties, including shale volume, porosity, and fluid saturation, based on a common set of well logs, including gamma ray, bulk density, neutron porosity, resistivity, and sonic. Log data from nine wells from the same field, together with the interpreted reservoir properties by petrophysicists, were provided as training data, and five additional wells were provided as blind test data. During the contest, various data-driven models were developed by the contestants to predict the three reservoir properties with the provided training data set. The top five performing models from the contest, on average, beat the performance of the benchmarked Random Forest model by 45% in the root-mean-square error (RMSE) score. In the paper, we will review these top-performing solutions, including their preprocessing techniques, feature engineering, and machine-learning models, and summarize their advantages and conditions.","PeriodicalId":170688,"journal":{"name":"Petrophysics – The SPWLA Journal of Formation Evaluation and Reservoir Description","volume":"21 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139686603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating the Usefulness of Least Squares Regression in Petrophysics Interpretation","authors":"Lee Etnyre","doi":"10.30632/pjv65n1-2024a4","DOIUrl":"https://doi.org/10.30632/pjv65n1-2024a4","url":null,"abstract":"This paper is to update the information provided in the author’s previous papers on evaluating the uncertainty in least squares results. It is prompted by new information that shows that the usefulness of any least squares result cannot be guaranteed by conventional statistics (such as R-squared, F-statistic, or standard error of the regression, sigma). A new method based on the singular value decomposition (SVD) of a matrix, when accompanied by a Relative Error Bound (REB) on the estimated parameters, provides the user with a tool that can better assess the usefulness of any least squares result. Another important aspect of the REB is that it provides the user of the SVD method with a powerful tool for judging which is the best among several candidate solutions. In addition, it provides the user with a numerically stable method of computing the data ordinarily provided by principal component regression by eliminating the need to perform an eigenvector-eigenvalue analysis of an ATA matrix. This is of particular interest because forming the ATA matrix is often accompanied by a loss of data. The new method also provides the user with an improved method for selection of which principal components should be retained for a given problem.","PeriodicalId":170688,"journal":{"name":"Petrophysics – The SPWLA Journal of Formation Evaluation and Reservoir Description","volume":"85 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139823030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Study on Rock Mechanics Parameter Prediction Method Based on DTW Similarity and Machine-Learning Algorithms","authors":"Wenjun Cai, Jianqi Ding, Zhong Li, Zhiming Yin, Yongcun Feng","doi":"10.30632/pjv65n1-2024a7","DOIUrl":"https://doi.org/10.30632/pjv65n1-2024a7","url":null,"abstract":"Rock mechanics parameters are crucial factors for predicting rock behavior in oil and gas reservoirs, optimizing extraction strategies, and ensuring drilling safety. In this study, we propose a random forest (RF)-convolutional neural network (CNN)-long-term short-term memory network (LSTM) fusion model based on the dynamic time warping (DTW) algorithm to construct intelligent prediction models for elastic modulus, Poisson’s ratio, and compressive strength using real-time drilling engineering data. An autoencoder with a sliding window is employed to automatically identify abnormal points or segments in the calculated values of elastic modulus, Poisson’s ratio, and compressive strength obtained from drilled wells. These abnormal values are then corrected using a backpropagation (BP) neural network. Compared to single CNN-LSTM or single RF models, the RF-CNN-LSTM fusion model performs better. It achieves this by effectively combining the strengths of different algorithms in predicting outcomes. The accuracy of the RF-CNN-LSTM fusion model is over 94% when compared to the actual values. Furthermore, the analysis of the relative importance of input parameters reveals that weight on bit (WOB), temperature, displacement, equivalent circulation density (ECD), and mud density are the primary input features for predicting elastic modulus. For predicting Poisson’s ratio, the main input features include WOB, mud density, ECD, temperature, pumping pressure, displacement, and rate of penetration (ROP). Similarly, for predicting compressive strength, the main input features consist of WOB, temperature, displacement, ECD, and mud density. The research findings demonstrate that the rock mechanics parameter prediction models based on the RF-CNN-LSTM algorithm using DTW exhibit high computational accuracy in the B oil field of China. These results are significant for gaining a deeper understanding of the variations in rock mechanics parameters and optimizing drilling decisions.","PeriodicalId":170688,"journal":{"name":"Petrophysics – The SPWLA Journal of Formation Evaluation and Reservoir Description","volume":"23 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139879659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experimental Research on the Permeability of Granite Under Different Temperature Cycles","authors":"Li Yu, Haonan Li, Yue Wu, Weihao Wang, Xinyuan Zhang, Yongchuan Zhao","doi":"10.30632/pjv65n1-2024a5","DOIUrl":"https://doi.org/10.30632/pjv65n1-2024a5","url":null,"abstract":"In this paper, through the permeability test of granite under different temperature cycles, the change law of porosity and permeability of rock samples after different temperature cycles was studied, and the relationship between the P-wave velocity and porosity and permeability was established by regression analysis. The results show that the porosity and permeability of the granite samples decreased significantly in one to three high-temperature cycles, showing a logarithmic change, and with the increase of the number of cycles, the decreasing rate gradually decreased after five to 10 thermal cycles, which is beneficial to the long-term development of deep geothermal resources. Under thermal cycles at different temperatures, the P-wave velocity of granite has a logarithmic correlation with permeability and porosity. As the number of cycles increases, the relationship between permeability, porosity, and P-wave velocity changes from a logarithmic relationship between one to three cycles to a linear relationship between five to 10 cycles. After thermal cycle treatment at different temperatures, there is an excellent logarithmic relationship between the P-wave velocity and porosity and permeability, and it has a high correlation. The porosity and permeability of granite can be estimated nondestructively by measuring the wave velocity. Using a scanning electron microscope (SEM) to observe the granite at 450℃, trivial particles appeared between the pore structure, and the internal structure of the rock sample was destroyed under the action of the thermal cycle. The change mechanism of physical property deterioration in deep geothermal energy mining is revealed, guiding deep geothermal energy mining.","PeriodicalId":170688,"journal":{"name":"Petrophysics – The SPWLA Journal of Formation Evaluation and Reservoir Description","volume":"162 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139820140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fluid Contamination Transient Analysis","authors":"Camilo Gelvez, C. Torres‐Verdín","doi":"10.30632/pjv65n1-2024a2","DOIUrl":"https://doi.org/10.30632/pjv65n1-2024a2","url":null,"abstract":"Successful in-situ fluid cleanup and sampling operations are commonly driven by a fast and reliable analysis of pressure, rate, and fluid contamination measurements. Techniques such as pressure transient analysis (PTA) provide important information to quantify reservoir complexity, while fluid contamination measurements are commonly overlooked for reservoir description purposes. We introduce a new interpretation technique to relate fluid contamination measurements with near-wellbore fluid-transport properties by identifying early- and late-time flow regimes in fluid contamination and its derivative function. The derivative methods used in PTA inspired the development of the new fluid contamination interpretation method. Contamination transient analysis (CTA) evaluates transient measurements acquired during cleanup of mud-filtrate invasion to infer important reservoir flow conditions. Center-point derivative methods are applied to the fluid pumpout volume and time evolution of fluid contamination to identify flow regimes in cases of water-based mud invading either water- or hydrocarbon-bearing formations. We document synthetic examples of the new interpretation method for seven reservoir cases, numerically simulated to obtain contamination data, namely, homogeneous isotropic reservoir, radial boundaries, vertical boundaries, thin-laminated formations, mud-filtrate invasion radius, petrophysical properties, and permeability anisotropy. Single-phase flow and multiphase flow cases are also compared in the analysis. Reservoir boundaries and features are identified in the flow regimes obtained from the combined interpretation of the fluid contamination derivative (FCD) and the log-log plot of the contamination transform. The seven reservoir cases assume fixed reservoir and operational parameters, such as reservoir geometry, rock properties, fluid properties, invasion radius, time of invasion, maximum pumpout rate, and maximum drawdown pressure, to allow for a controlled sensitivity analysis enabling the identification of cleanup trends. It is emphasized that real-time field conditions could trigger certain limitations of the transient techniques developed in this work, such as noisy downhole formation testing measurements, active mud-filtrate invasion, or tool failure. To validate the assumptions, observations, and results of the numerical simulations, a field case is examined to (a) highlight the value of CTA in real-time fluid sampling operations and (b) further investigate its limitations. An alternative validation of the method is performed by applying the derivative directly to the formation testing measurements during fluid cleanup, reducing the uncertainty in the contamination estimation and the interpretation of transient trends. The new approach of the FCD is an alternative to improve fluid cleanup efficiency and to detect the spatial complexity of the reservoir during real-time downhole fluid sampling. Using log-log plots of fluid contaminati","PeriodicalId":170688,"journal":{"name":"Petrophysics – The SPWLA Journal of Formation Evaluation and Reservoir Description","volume":"23 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139886030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fluid Contamination Transient Analysis","authors":"Camilo Gelvez, C. Torres‐Verdín","doi":"10.30632/pjv65n1-2024a2","DOIUrl":"https://doi.org/10.30632/pjv65n1-2024a2","url":null,"abstract":"Successful in-situ fluid cleanup and sampling operations are commonly driven by a fast and reliable analysis of pressure, rate, and fluid contamination measurements. Techniques such as pressure transient analysis (PTA) provide important information to quantify reservoir complexity, while fluid contamination measurements are commonly overlooked for reservoir description purposes. We introduce a new interpretation technique to relate fluid contamination measurements with near-wellbore fluid-transport properties by identifying early- and late-time flow regimes in fluid contamination and its derivative function. The derivative methods used in PTA inspired the development of the new fluid contamination interpretation method. Contamination transient analysis (CTA) evaluates transient measurements acquired during cleanup of mud-filtrate invasion to infer important reservoir flow conditions. Center-point derivative methods are applied to the fluid pumpout volume and time evolution of fluid contamination to identify flow regimes in cases of water-based mud invading either water- or hydrocarbon-bearing formations. We document synthetic examples of the new interpretation method for seven reservoir cases, numerically simulated to obtain contamination data, namely, homogeneous isotropic reservoir, radial boundaries, vertical boundaries, thin-laminated formations, mud-filtrate invasion radius, petrophysical properties, and permeability anisotropy. Single-phase flow and multiphase flow cases are also compared in the analysis. Reservoir boundaries and features are identified in the flow regimes obtained from the combined interpretation of the fluid contamination derivative (FCD) and the log-log plot of the contamination transform. The seven reservoir cases assume fixed reservoir and operational parameters, such as reservoir geometry, rock properties, fluid properties, invasion radius, time of invasion, maximum pumpout rate, and maximum drawdown pressure, to allow for a controlled sensitivity analysis enabling the identification of cleanup trends. It is emphasized that real-time field conditions could trigger certain limitations of the transient techniques developed in this work, such as noisy downhole formation testing measurements, active mud-filtrate invasion, or tool failure. To validate the assumptions, observations, and results of the numerical simulations, a field case is examined to (a) highlight the value of CTA in real-time fluid sampling operations and (b) further investigate its limitations. An alternative validation of the method is performed by applying the derivative directly to the formation testing measurements during fluid cleanup, reducing the uncertainty in the contamination estimation and the interpretation of transient trends. The new approach of the FCD is an alternative to improve fluid cleanup efficiency and to detect the spatial complexity of the reservoir during real-time downhole fluid sampling. Using log-log plots of fluid contaminati","PeriodicalId":170688,"journal":{"name":"Petrophysics – The SPWLA Journal of Formation Evaluation and Reservoir Description","volume":"180 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139825854","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}