Mitigating Liquid Loading in Gas Wells Using Thermochemical Fluid Injection: An Experimental and Simulation Study.

Liquid loading significantly hinders gas production in unconventional shale wells, restricting flow and causing productivity decline. This study presents a novel approach to address this challenge, utilizing thermochemical fluids to generate in situ pressure and heat and effectively mitigating liquid loading issues. Laboratory experiments were conducted using a specially designed flow loop system to evaluate the performance of thermochemical fluids in alleviating liquid loading. The key treatment parameters such as thermochemical volumes, injection rate, number of cycles, and optimum injection time were optimized to improve the removal efficiency. In addition, PIPESIM software (pipe simulation program) was used to validate the effectiveness of the thermochemical approach for removing the liquid loading issue. Both laboratory results and PIPESIM outcomes confirmed the efficiency of thermochemical fluids in handling liquid loading. Removal efficiency of more than 90% can be achieved using thermochemical injection. The liquid removal efficiency increases with the number of cycles due to the generation of more pressure and heat at later injection cycles. Increasing injection cycles from 1 to 3 resulted in liquid removal efficiency rising from 17 to 95%. Also, PIPESIM results indicated that the gas production rate can be improved by around 74% after applying thermochemical treatment. Overall, this study introduces an effective treatment for liquid loading mitigation with significant potential to enhance gas production. The proposed method offers several advantages, including ease of application and extended well life.

Prediction of Total Organic Carbon in Organic-Rich Shale Rocks Using Thermal Neutron Parameters.

Total organic carbon (TOC) content is one of the crucial parameters that determine the value of the source rock. The TOC content gives important indications about the source rocks and hydrocarbon volume. Various techniques have been utilized for TOC quantification, either by geochemical analysis of source rocks in laboratories or using well logs to develop mathematical correlations and advanced machine learning models. Laboratory methods require intense sampling intervals to have an accurate understanding of the reservoir, and depending on the thickness of the interested formation, it can be time-consuming and costly. Empirical correlations based on well logs (e.g., density, sonic, gamma ray, and resistivity) showed fast predictions and very reasonable accuracies. However, other important parameters such as thermal neutron logs have not been studied yet as a potential input for providing reliable TOC predictions. Also, different studies estimate the TOC based on the well-logging data for various formations; however, limited studies were reported to predict the TOC for the Horn River Formation. Therefore, the objective of this study is to estimate the TOC variations based on the thermal neutron logs using one of the largest source rocks in Canada: The Horn River Formation. More than 150 data sets were collected and used in this work. The parameters of the artificial neural network (ANN) model were fine-tuned in order to improve the model's prediction performance. Furthermore, an empirical correlation was developed utilizing the optimized ANN model to allow fast and direct application for the developed model. The developed correlation can predict the TOC with an average absolute error of 0.52 wt %. The proposed TOC model was able to outperform the previous models, and the coefficient of determination was increased from 0.28 to 0.73. Overall, the proposed TOC model can provide high accuracy for TOC ranges from 0.3 to 6.44 wt %. The developed model can provide a real-time quantification for the organic matter maturity, helping to allocate the zones of mature organic matter within the drilled formations.

Impact of Asphaltene Precipitation and Deposition on Wettability and Permeability.

Asphaltene precipitation and deposition have been a formation damage problem for decades, with the most devastating effects being wettability alteration and permeability impairment. To this effect, a critical look into the laboratory studies and models developed to quantify/predict permeability and wettability alterations are reviewed, stating their assumptions and limitations. For wettability alterations, the mechanism is predominantly surface adsorption, which is controlled by the asphaltene contacting minerals as they control the surface chemistry, charge, and electrochemical interactions. The most promising wettability alteration evaluation techniques are nuclear magnetic resonance, ζ potential, and the use of high-resolution microscopy. The integration of such techniques, which is still missing, would reinforce the understanding of asphaltene interaction with rock minerals (especially clays), which holds the key to developing a strategy for modeling wettability alteration. With regard to permeability impairment, surface deposition, pore plugging, and fine migration have been identified as the dominant mechanisms with several models reporting the simultaneous existence of multiple mechanisms. Existing experimental findings showed that asphaltene deposition is non-uniform due to mineral distribution which further complicates the modeling process. It also remains a challenge to separate changes due to adsorption (wettability changes) from those due to pore size reduction (permeability impairment).

The Effect of Clay Content on the Spin-Spin NMR Relaxation Time Measured in Porous Media.

Clays, hydrous aluminous phyllosilicates, have a significant impact on the interpretation of physical measurements and properties of porous media. In particular, the presence of paramagnetic and/or ferromagnetic ions like iron, nickel, and magnesium in clays can complicate the analysis of nuclear magnetic resonance (NMR) data for porous media characterization. This is due to the internal magnetic field gradient induced by the clay minerals. In this study, we aim to investigate the impact of clay content on spin-spin relaxation time (T 2), which is strongly influenced by the pore surface chemistry. Seven rock core plugs, characterized with variable clay content, were used for this purpose. The clay mineralogy and volume were determined by means of quantitative evaluation of minerals by scanning electron microscopy (QEMSCAN). The T 2 relaxation time was measured using a Carr-Purcell-Meiboom-Gill (CPMG) sequence with variable echo spacing (T E). The maximum percentage difference in dominant T 2 values (MRDT 2) between shortest and longest echo spacing was subsequently correlated with clay content obtained from QEMSCAN. Our results show that the reduction in T 2 distribution with increasing echo time T E is more significant in samples characterized by higher clay contents. The MRDT 2 was found to be strongly correlated with clay content. An analytical equation is presented expressing MRDT 2 as a function of clay content providing a quick and non-destructive approach for clay content estimation. Moreover, the MRDT 2-clay content relationship showed a nonlinear behavior: MRDT 2 increases drastically as the clay content increases up to 15%, beyond which the rate of MRDT 2 change with clay content diminishes. This behavior could be attributed to the clay distribution. At higher clay contents (above 15%), it is more likely for clay to form clusters (structural clays), which will not significantly increase the clay surface in contact with the pore fluid. Further, experimental data suggests that ignoring the impact of clay on internal magnetic gradients and T 2 signal may result in considerable underestimation of the actual pore size distribution.