The measurement and interpretation methodology of resistivity logs affected by the Groningen effect – a Polish case study

True formation resistivity Rt measurement is one of the fundamental logs in the calculation of hydrocarbon resources. That is why it is very important to have the most reliable resistivity data possible. In this paper, the various outcomes obtained by Polish well log analysts and engineers for the proper determination of hydrocarbon saturation in the Main Dolomite deposits in the Polish Lowland are presented. The long history of efforts directed to make proper exploitation decisions in wells where the Groningen effect has been observed is illustrated, starting with the standard measurement and interpretational approach, through the modified construction of a reference electrode in a Laterolog device and ending with an examination of HRLA (High-Resolution Laterolog Array) or Array Compensated Resistivity Tool) ACRt results. The processing of resistivity logs with the special Poprawki software is included

Research results of triaxial geomechanical tests of a coal sample in the light of tomographic tests

The study aimed to check the possibility of using computed tomography to observe fractures in coal samples before and after a triaxial compression test (TRX). The paper presents an innovative use of two specialized laboratory techniques: computed tomography and geomechanical triaxial compression test. Geomechanical tests were performed on a TRX-070, GCTS (USA) measuring triaxial system. A full stress-strain characteristic was recorded. Also, during the triaxial compression tests, the P and S wave velocities were measured and dynamic elastic moduli were determined. The results were compared. The sample was analyzed in two stages: CT measurement performed on raw coal sample (stage 1) and after the TRX test which destroyed the sample structure (stage 2). First, the sample was scanned reflecting the initial pores and microcracks system. The final stage represents the sample after the geomechanical test. A detailed pore structure analysis was performed for each of the stages. As a result of the proposed above-mentioned method, images of the pore structure were obtained after each step. The sample was analyzed for crack propagation and changes in the pore structure. The qualitative and quantitative interpretation was based on the determination of the number of voids, crack diameters, collapse angles, and comparison of the pore structure between the initial state of the sample and after the triaxial test. In the first stage (before the test), the largest object (identified as a microcrack) had a volume of approximately 16 mm3, after the sample was stress-tested (after the sample was destroyed), the largest identified object was about 15 times larger (240 mm3). It appeared that the coal sample was prone to fracturing in defined directions. Comprehensive research has demonstrated the legitimacy of using the proposed methodology to evaluate changes in the sample structure during the triaxial test

Shale Gas in Poland

An example of interpretation of the Silurian and Ordovician shale formations in the Baltic Basin in Poland regarding determination of potential sweet spots is presented. Short geological information shows the position of shale gas play. Description of the data—laboratory measurement outcomes (petrophysical and geochemical) and well logging—presents results available for analyses. Detailed elemental analyses and various statistical classifications show the differentiation between sweet spots and adjacent formations. Elastic property modelling based on the known theoretical models and results of comprehensive interpretation of well logs is a good tool to complete information, especially in old wells. Acoustic emission investigations show additional characteristic features of shale gas rock and reveal that acoustic emission and volumetric strain of a shale sample induced by the sorption processes are lower for shale than for coals

Application of Multivariate Statistical Methods and Artificial Neural Network for Facies Analysis from Well Logs Data: an Example of Miocene Deposits

The main purpose of the study is a detailed interpretation of the facies and relate these to the results of standard well logs interpretation. Different methods were used: firstly, multivariate statistical methods, like principal components analysis, cluster analysis and discriminant analysis; and secondly, the artificial neural network, to identify and discriminate the facies from well log data. Determination of electrofacies was done in two ways: firstly, analysis was performed for two wells separately, secondly, the neural network learned and trained on data from the W-1 well was applied to the second well W-2 and a prediction of the facies distribution in this well was made. In both wells, located in the area of the Carpathian Foredeep, thin-layered sandstone-claystone formations were found and gas saturated depth intervals were identified. Based on statistical analyses, there were recognized presence of thin layers intersecting layers of much greater thickness (especially in W-2 well), e.g., section consisting mainly of claystone and sandstone formations with poor reservoir parameters (Group B) is divided with thin layers of sandstone and claystone with good reservoir parameters (Group C). The highest probability of occurrence of hydrocarbons exists in thin-layered intervals in facies C

Applying of the Artificial Neural Networks (ANN) to Identify and Characterize Sweet Spots in Shale Gas Formations

The main goal of the study was to enhance and improve information about the Ordovician and Silurian gas-saturated shale formations. Author focused on: firstly, identification of the shale gas formations, especially the sweet spots horizons, secondly, classification and thirdly, the accurate characterization of divisional intervals. Data set comprised of standard well logs from the selected well. Shale formations are represented mainly by claystones, siltstones, and mudstones. The formations are also partially rich in organic matter. During the calculations, information about lithology of stratigraphy weren’t taken into account. In the analysis, selforganizing neural network – Kohonen Algorithm (ANN) was used for sweet spots identification. Different networks and different software were tested and the best network was used for application and interpretation. As a results of Kohonen networks, groups corresponding to the gas-bearing intervals were found. The analysis showed diversification between gas-bearing formations and surrounding beds. It is also shown that internal diversification in sweet spots is present. Kohonen algorithm was also used for geological interpretation of well log data and electrofacies prediction. Reliable characteristic into groups shows that Ja Mb and Sa Fm which are usually treated as potential sweet spots only partially have good reservoir conditions. It is concluded that ANN appears to be useful and quick tool for preliminary classification of members and sweet spots identification

Ocena własności zbiornikowych skał przy wykorzystaniu zjawiska magnetycznego rezonansu jądrowego : praca doktorska /

Recenzenci pracy: Maria Ciechanowska, Maria Bała.Praca doktorska. Akademia Górniczo-Hutnicza im. Stanisława Staszica (Kraków), 2011.Bibliogr. k. 128-136.Metoda magnetycznego rezonansu jądrowego, magnetyczny rezonans jądrowy, opis kwantowo-mechaniczny, opis klasyczny, relaksacja, równania Blocha, warunek rezonansu, sygnał swobodnej precesji, metoda echa spinowego, NMR w badaniach własności skał, materiały, metody, opis litologii, stratygrafii próbek skał wybranych do analizy, utwory klastyczne, węglanowe, aparatura pomiarowa, budowa spektrometru Maran Ultra, oprogramowanie, procedury pomiarowe, dobór parametrów pomiarowych, przeprowadzone serie pomiarowe, inne metody pomiarowe wykorzystane do analizy, badania laboratoryjne parametrów petrofizycznych, zestawienie wyników, porozymetria rtęciowa, opis metody, wyniki pomiarów, analiza wyników, interpretacja, analiza rozkładu nasyceń metodą NMR, połączenie wyników NMR, MP, analiza sygnałów NMR pod kątem dopasowania do krzywych teoretycznych, wyznaczanie czasów odcięcia, program dystrybucja, sygnały skumulowane, znormalizowane, rozdzielenie mikro- mezo-, makro- porowatości, podział porów, wyznaczenie przepuszczalności, ocena przepuszczalności na podstawie modeli, parametru Swanson

Comparative analysis of rock porosity in a selected region in the Carpathians based on laboratory data and well logs

A comparative analysis of porosity is presented in the article. This was calculated from laboratory measurements and well logs for rocks from a selected region of the Carpathians. Analysis was performed for samples of sandstones, mudstones, shales and carbonates from four boreholes drilled in the Carpathian Foredeep region near Krakow, Poland. In laboratory measurements, porosity was assessed using two methods: helium pycnometry and nuclear magnetic resonance (NMR). Porosity from well logging was calculated from sonic profiling (SPHI). Cross-plots were used, which allowed for the assessment of the degree of correlation between the laboratory and well log data. The results obtained were analysed paying special attention to the relationship with geological structure. Based on the lithological criterion, the correlations turned out to be strong. The repeatability of the results obtained in different wells was verified. The results of the measurements are significant in relation to estimating porosity from well logs using laboratory data

Comparative analysis of rock porosity in a selected region in the Carpathians based on laboratory data and well logs

A comparative analysis of porosity is presented in the article. This was calculated from laboratory measurements and well logs for rocks from a selected region of the Carpathians. Analysis was performed for samples of sandstones, mudstones, shales and carbonates from four boreholes drilled in the Carpathian Foredeep region near Krakow, Poland. In laboratory measurements, porosity was assessed using two methods: helium pycnometry and nuclear magnetic resonance (NMR). Porosity from well logging was calculated from sonic profiling (SPHI). Cross-plots were used, which allowed for the assessment of the degree of correlation between the laboratory and well log data. The results obtained were analysed paying special attention to the relationship with geological structure. Based on the lithological criterion, the correlations turned out to be strong. The repeatability of the results obtained in different wells was verified. The results of the measurements are significant in relation to estimating porosity from well logs using laboratory data

Electrofacies as a Tool for the Prediction of True Resistivity Using Advanced Statistical Methods—Case Study

Statistical analysis methods have been widely used in all industries. In well logs analyses, they have been used from the very beginning to predict petrophysical parameters such as permeability and porosity or to generate synthetic curves such as density or sonic logs. Initially, logs were generated as simple functions of other measurements. Then, as a result of the popularisation of algorithms such as the k-nearest neighbours (k-NN) or artificial neural networks (ANN), logs were created based on other logs. In this study, various industry and general scientific programmes were used for statistical data analysis, treating the well logs data as individual data sets, obtaining very convergent results. The methods developed for processing well logs data, such as Multi-Resolution Graph-Based Clustering (MRGBC), as well as algorithms commonly used in statistical analysis such as Kohonen self-organising maps (SOM), k-NN, and ANN were applied. The use of the aforementioned statis-tical methods allows for the electrofacies determination and prediction of an Rt log based on the other recorded well logs. Correct determination of Rt in resistivity measurements made with the Dual Laterolog tool in the conditions of the Groningen effect is often problematic. The applied calculation methods allow for the correct estimation of Rt in the tested well