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Abstract The formation evaluation of low-porosity tight gas reservoirs in Argentina presents several well-known challenges in the estimation of main petrophysical properties as porosity, clay fraction, permeability, and water saturation. The main goal is to accurately quantify these petrophysical properties with a consistent and reliable petrophysical model. The next task is to reveal the key petrophysical responses that represent the link between petrophysics and production. The present work describes the main petrophysical challenges faced and an innovative workflow used in the Lindero Atravesado field with clear examples to illustrate the effectiveness of this approach. The workflow involves measurements such as advanced elemental gamma ray spectroscopy, multifrequency dielectric dispersion, and nuclear magnetic resonance (NMR). The advanced elemental gamma ray spectroscopy has been key for the creation of a robust mineralogical model, and to derive the matrix properties used to obtain an accurate porosity free of matrix and gas effects with the combination of NMR porosity. The dielectric dispersion provides a direct estimation of water volume, which, in turn, helps to adjust the conventional method of water saturation from resistivity. The good correlation between the petrophysical properties estimated from the proposed workflow and the core analysis, demonstrates the benefits of using the advanced log measurements. The final step of the workflow consists in the definition of poro-fluid facies determined with a new methodology, called NMR factor analysis, that is based on the extraction of multimodal information from the NMR T2 distribution to determine the optimal number of dominant modes (factors) that allow describing the reservoir. Production logging results showed a good relationship between the poro-fluid facies and reservoir productivity.
Abstract An accurate permeability value for a tight gas reservoir has become an important need in the natural gas industry. However, there have been and there are still many ways to calculate this variable, but has low reliability, since permeability in many cases does not follow a linear behavior. For that reason, were here implemented the integration, operation, and optimization of linear methods (empirical, statistical multiple regression) and nonlinear methods (primarily neural networks) in order to improve the permeability prediction of Lajas Formation, using cores and well logs. The aim of this paper is to present the results of the combination of linear methods (e.g. empirical and multiple regressions) with nonlinear methods called The Artificial Neural Network (Multilayer Perceptron Model) to which we call Hybrid model applied to reservoirs with tight gas features, in order to predict a continuous curve of permeability (for wells that do not have core or well logs information). The porosity has been taken from different curves: gamma ray (GR), resistivity (RD), neutron (NPHI), density (PHID), (RHOB), and each were adjusted to the porosity data obtained by core samples and sidewall cores. This method allowed validating and optimizing the petrophysical model. This study was focused on Lajas Formation that belongs to the Cuyo Group (Lower to Middle Jurassic) in the Neuquen Basin. This geologic unit consists of gray sandstones of medium to fine grained with interbedded conglomerates, limestones and lenticular shales of varying thickness. All data were collect from public sources and were processed for the present research.
Abstract One of today challenges to increase reserves and gas production in Argentina is to develop low permeability reservoirs, with particular characteristics regarding reservoirs considered as conventional. Therefore assessment and characterization of tight gas reservoirs should be conducted differently from conventional reservoirs, adapting data acquisition, processing and interpretation to these low permeability reservoirs. In a tight gas field operated by Petrobras in the Neuquen basin, an adapted methodology is implemented for analysis and integration of data in order to identify the best areas of the reservoir, called "sweet spots", to assess their potential and optimize completion programs. The field has 7 wells with data acquired from the 70's to recent days. Petrophysical analyses on rock samples are scarce and unrepresentative related to the total sand thickness of Punta Rosada Formation, and were conducted with an inappropriate methodology for this type of reservoir. The set of logs shows strong variation both in used technology and in the acquisition. Thus in new wells it has been decided to acquire new logs and rock samples in order to characterize these tight gas reservoirs with an adapted methodology allowing the identification of the "sweet spots". This paper shows the results obtained with this methodology that uses information from petrophysical laboratory analysis and well-logs (including conventional logs, image logs and NMR). This "tight gas" methodology is based on the integration among capillaries pressures with NMR logs and interpreted data from conventional logs. Finally, to validate this petrophysical characterization, the rock types obtained with the new methodology are compared with the results of production tests and PLT logs.
Maza, Daniel (YPF) | Oggier, Fabian P. (YPF) | Do Nascimento, Carlos (YPF) | Saldungaray, Pablo J. (Schlumberger) | Zambrano, Rafael (Schlumberger) | Mosse, Laurent (Schlumberger) | Anci, Pablo B. (Schlumberger) | Barrionuevo, Pablo (Schlumberger)
Abstract An alternative technique to evaluate layered formations through casing in the Golfo San Jorge basin in Argentina is presented. The proposed methodology is based on pulsed neutron spectroscopy logs to assess the lithology and evaluate the hydrocarbon type and potential using resistivity-independent methods. The basin's layered reservoirs present multiple challenges for resistivity-based methods, including low and variable formation water salinity, intricate pore systems affecting the rock electrical parameters, fine sediments with high irreducible water content suppressing the resistivity response, and high-resistivity tuffaceous sands not associated with hydrocarbons. In cased holes, simple correlations of resistivity and capture cross-section (sigma) or other techniques emulating openhole logs from basic pulsed neutron logs (PNL) can be used for interwell correlations, but are frequently inconclusive for assessing hydrocarbon potential. Our approach takes advantage of latest-generation PNL tools’ multiple measurements to reduce the uncertainty of water saturation assessment. The proposed methodology was tested with two new-generation PNL tools, which feature high-resolution detectors that provide elemental concentrations for better understanding mineralogy including direct measurement of the carbon concentration for a reliable estimation of total organic carbon (TOC), which is directly associated with the oil volume in the pore space. The first tool was originally intended for openhole logging and has a single large detector for high-quality spectroscopy analysis. The second device is a multiple-detector slim PNL tool, which, besides the TOC and other spectroscopy outputs, also provides sigma and neutron porosity and measures a new property, the fast neutron cross section (FNXS), which is useful to detect and quantify gas. The presented case studies include examples of application with both tools in new wells and workovers. More than 20 sands, typically 2- to 5-m thick, interbedded with thick shales, were counted over the 1000- to 1500-m zone of interest, and all the data could be acquired in an acceptable time frame in spite the long intervals. The log data were complemented with the mud logging information and/or correlations from the static geological model. In all cases, we achieved good correlation between the zones with TOC, the static model, and well test results. This experience illustrates the adaptation and application of new technologies to the development of mature fields where conventional openhole resistivity-based analysis is ambiguous. Future tasks include adjusting the technique for quantitative analysis and its use in deeper, more challenging, unconventional reservoirs in the basin.
Abstract Geopressures modeling has become a critical task in unconventional plays since the high pore pressures found in some areas makes drilling and completion operations particularly challenging. This field study helped to quantify the pore pressure anomalies and understanding the overpressure mechanisms acting in the tight gas reservoir of Rio Neuquen field. To achieve this objective a pore pressure model was built based on seismic attributes and multi well data analysis. This model also helped to establish possible relationships between reservoir performance and those pore pressure anomalies. The mathematical model used seismic velocities from PSDM tomography and simultaneous inversion for establishing relationships between the elastic rock response and pore pressure, through a series of effective stress-velocity transforms. The model also considers a multi variable analysis to account for other variables affecting seismic response, including porosity, VSH and effective stress, like that proposed by Sayers (2003). Field data from several wells was used to tie the seismic velocities to well logs, while laboratory tests and pressure measurements were used as calibration points for the model, supporting the results of the study. The analysis showed that interval velocities from seismic inversion led to a more representative and accurate pore pressure model than that obtained from the PSDM velocities. The analysis showed that velocity reversals from seismic had a strong stress influence while as confirmed later by ultrasonic lab test analysis and observed pressure data. There were also some lithological and porosity effects in the elastic response of seismic, as evidenced by well logs. This, however, could not be modeled at field scale due to limitations in the available 3D seismic data. Pore pressure anomalies are expected to be highly influenced by the presence of a nearby overpressurized source rock. The study suggests indeed that that multiple type II overpressure mechanisms can be present in the area, including lateral transfer, HC generation and tectonic load. The model showed that the pressure anomalies are higher as closer is the reservoir to the source rock. Four new wells drilled in the recent campaign probed the accuracy and robustness of the pore pressure predictions. This work is an excellent case study that shows how pore pressure can be modeled in some tight sands that exhibits a stress sensitive behavior. The pore pressure model helped to evaluate not only gas reserves but also sweet spots, making the 3D pore pressure prediction a powerful tool for exploration, drilling and field development planning.