مجله ژئومکانیک نفت
سال هفتم شماره 1 (بهار 1403)

One of the most important tasks of the drilling fluid is to maintain and provide the stability of the well. Low pressure inside the well can lead to the collapse of the wall or the unwanted entry of fluid into the well. On the other hand, the high pressure inside the well can lead to the failure of the well wall; Therefore, the appropriate value of drilling fluid density should be selected so that the pressure inside the well remains at equilibrium. The Objectives of this research is to determine the density of drilling fluid according to the concept of wellbore stability so that the radial and tangential stresses in the well wall are equal. For this purpose, first the required data were collected from one of the field wells in the southwest of Iran. Then, the induced stresses in the well wall were calculated using the existing relations. The results of this study showed that according to the safe window of drilling fluid density, the maximum and minimum optimal fluid density in which the stability of the well will be maintained at the desired depths will be 16.80 and 13.93 pounds per gallon, respectively. Also, the comparison of the optimal density and the actual density used in the drilling fluid of this well showed that due to the fact that the actual density used in the operation was lower than the optimal density, problems of instability of the well wall were observed at different depths.

Evaluating the characteristics of carbonate reservoirs, given their significant heterogeneity, is always accompanied by challenges and high uncertainties. Water saturation is a crucial parameter in assessing these reservoirs, and the Archie equation is commonly used for water saturation estimation. Moreover, the effect of water saturation on the mechanical behavior of rock is recognized as an important phenomenon in geotechnical engineering. The accuracy of water saturation calculated through the Archie equation depends on the precision of its parameters, including cementation exponent, saturation exponent, and tortuosity exponent. The heterogeneity of carbonate reservoirs significantly affects the Archie equation coefficients and, consequently, water saturation calculations. In this study, various methods, including the electrical efficiency, current zone indicator, and Winland method, were employed to manage reservoir heterogeneity. Subsequently, Archie parameters were calculated for each category, and water saturation was determined and compared with Dean-Stark water saturation. Furthermore, the influential parameters on the accuracy of water saturation were discussed and examined. To achieve the study objectives, 157 Dean-Stark water saturation data, 57 core plug samples for formation resistivity factor (FRF) determination, 20 core plug samples for measuring formation resistivity index (FRI), 1114 porosity and permeability measurements from core plug samples and 1368 thin sections were utilized from an exploration well in the western Gulf of Persian. Our findings highlight the significance of exploring electrical behavior characteristics and pore throat radii as crucial elements influencing the precision of water saturation calculations. As per the results, employing constant Archie parameters leads to an overestimation of water saturation and, consequently, an underestimation of hydrocarbon reserves. Our analysis illustrates that effectively managing reservoir heterogeneity through the electrical efficiency method significantly improves the accuracy of predicted water saturation compared to other approaches. Conversely, the Winland method exhibits the highest uncertainty in predicting water saturation.

The high cost of drilling operations has led to increasing challenges in optimizing drilling operations. The key to success in reducing these costs is designing the well program based on the prediction of potential drilling issues and problems. Over the past few decades, the drilling industry has shown an increasing interest in machine learning to predict drilling problems. This paper presents a comprehensive review of studies related to the application of machine learning in predicting drilling hazard events. In each study, machine learning algorithms, the number of data points, input and output parameters to the machine and the performance of the corresponding algorithm are extracted from previous studies. In addition, limitations, similarities of the studies in each category are summarized and a review of the literature is provided along with recommendations for the development of future studies. These reviews show that the artificial neural network algorithm is the most popular method among the machine learning algorithms in the studies; Meanwhile, other algorithms such as support vector machine algorithm and random forest may show better performance in extracting results. It should also be noted that many of the intelligent models presented by researchers are based on limited samples and the specific conditions and may not be generalizable.

One of the most crucial and valuable resources accessible to humanity is underground resources. Their value is so significant that they exert control over the world economy. Drilling activities are indispensable for accessing these precious resources. Among the paramount factors in the realm of oil and gas well drilling is the rate of penetration of the drill bit. This study utilizes information from three wells located in an oil field in the southwest of Iran. The algorithms newly combined in this article comprise a fusion of the K-nearest neighbor algorithms, honey bee algorithm, firefly algorithm, and multilayer perceptron. This algorithm represents a novel and unique amalgamation of potent algorithms hitherto unused for predicting this vital parameter. Notably, this method excels at reducing data noise and enhancing the accuracy of parameter predictions. The results demonstrate that the mean square error for the testing and training data sets, as well as the entire dataset, stood at 1.05, 1.52, and 1.48, respectively. These figures underscore the algorithm's high-performance accuracy. Additionally, upon scrutinizing the Pearson's coefficient it was ascertained that drilling bits nozzles significantly influenced the penetration rate. Finally, researchers can use the algorithm introduced in this paper to predict other key reservoir, production, drilling, and geophysical parameters.

This study investigated the effect of various factors on the pore-throats, in a well in the upper Dalan and Kangan Formations in the central part of the Persian Gulf. Microfacies, sedimentary environments, dominant diagenetic processes on microfacies and the general effect of primary and secondary processes on the dispersion of porosity and permeability data, was investigated. Petrographic studies led to the identification of 12 microfacies in four facies belts in an epeiric carbonate platform environment. The grain dominant texture has higher values of porosity and permeability compared to the mud dominated texture. The most prevalent diagenetic processes are dolomitization, dissolution, cementation and compaction. The moldic, vuggy, intercrystalline and intergranular porosities are the most important identified pores. The study of the effects of each diagenetic process separately indicates the effect of the process of dissolution and dolomitization on increased the pore-throats and reservoir quality. Results showed that cementation and compaction alone do not have a reducing role and its greater effect is due to the combination of both factors. In order to investigate the effects of facies and diagenesis on the pore-throat, porosity and permeability data were plotted on the Winland diagram and seven rock types with different pore-throats were identified. Due to the effects of different diagenetic factors on the microfacies, the pore-throat sizes vary between same microfacies. The grain dominant facies (packstone and grainstone) belonging to the shoal facies belt, have the highest pore-throats and the best rock type determined by the Winland method. Plotting the porosity and permeability data in the Winland diagram has let to detection of 7 zones with different pore throat size, that samples with higher R35 are affected by dissolution and dolomitization and samples with lower R35 are affected by cementation and compaction.

Today, pilot wells are used for sampling the layers of the earth during deviation drilling. In order to reduce costs and facilitate operations in situations where it is not possible to use a pilot well for coring, coring studies are carried out in a deviant manner. Investigating the effect of drilling parameters on penetration rate in core drilling of deviated wells is important to optimize operations. In this regard, the rate of penetration is studied and simulated by preparing concrete samples for coring in a deviant way with laboratory devices, so that it reaches the most optimal state with the least amount of time, along with the necessary safety. In this research, cubic concrete samples with uniaxial compressive strength of 30 MPa and porosity of 31% have been used, and the effect of these parameters on the rate of penetration has been investigated by applying various weight on bit and angles of deviation. According to the experiments, the direct effect of the weight on bit on the penetration rate until reaching the turning point and the optimal value was observed. Also, by increasing the extra weight on bit, it causes a change in the mechanism of the bit's performance in drilling and loses its tangential state and causes the small particles of the sample to be torn off, which reduces the life of the drill bit.