Drilling issues such as shale hydration, high-temperature tolerance, torque and drag are often resolved by applying an appropriate drilling fluid formulation. Oil-based drilling fluid (OBDF) formulations are usually composed of emulsifiers, lime, brine, viscosifier, fluid loss controller and weighting agent. These additives sometimes outperform in extended exposure to high pressure high temperature (HPHT) conditions encountered in deep wells, resulting in weighting material segregation, high fluid loss, poor rheology and poor emulsion stability. In this study, two additives, oil wetter and rheology modifier were incorporated into the OBDF and their performance was investigated by conducting rheology, fluid loss, zeta potential and emulsion stability tests before and after hot rolling at 16 h and 32 h. Extending the hot rolling period beyond what is commonly used in this type of experiment is necessary to ensure the fluid’s stability. It was found that HPHT hot rolling affected the properties of drilling fluids by decreasing the rheology parameters and emulsion stability with the increase in the hot rolling time to 32 h. Also, the fluid loss additive’s performance degraded as rolling temperature and time increased. Adding oil wetter and rheology modifier additives resulted in a slight loss of rheological profile after 32 h and maintained flat rheology profile. The emulsion stability was slightly decreased and stayed close to the recommended value (400 V). The fluid loss was controlled by optimizing the concentration of fluid loss additive and oil wetter. The presence of oil wetter improved the carrying capacity of drilling fluids and prevented the barite sag problem. The zeta potential test confirmed that the oil wetter converted the surface of barite from water to oil and improved its dispersion in the oil.

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Converting data to actionable information through continuous oil production monitoring is a fundamental part of any production optimization strategy. The development of Intelligent Field technology has remarkably contributed to the upgrading of production surveillance framework and provided an extended access to real-time data. This same technology is still in its infancy when it comes to multiphase mass metering and field practicality issues. As for conventional fields where the unavailability of continuous data flow is not considered out of norm, the high uncertainty in oil production rate estimation and allocation is very well expected. The main source of this uncertainty is the reliance on sporadic welltest data and empirical multiphase flow correlations to allocate liquid production rate.Critical and subcritical multiphase flow choke performance is predicted using well-known correlations that are based on specific datasets characterized by a specific field or hydrocarbon type. Case studies where those correlations are matched with different production data and used later to predict the choke performance are present in the literature. Yet, the oil industry is faced with many challenges because of the limited accuracy of those predictions. The complexity of multiphase flow behavior and the irregularities in operational conditions can explain such low capability of those correlations particularly on field data.Artificial intelligence (AI) tools and techniques for so-called artificial neural networks, fuzzy logic and functional networks were employed to develop data-driven oil flow rate computational models for both critical and subcritical flow conditions. These AI models were trained and tested exploiting 595 production rate tests from 31 different wells. The prediction results showed a strong correlation with actual field data and promised a reliable tool/methodology to estimate oil flow rate as a function of operational conditions and choke size. This paper presents an engineering look at the inclusion of AI data-driven models in the production surveillance system to enhance welltest data validation and reduce the uncertainties in production allocation.

During hydrocarbon drilling operations, the presence of hydrogen sulfide (H2S) gas could cause serious health and safety issues. Scavenging this gas and eliminating its impact are essential requirements for a safe drilling operation. This study investigated the impact of three H2S scavenger additives (copper nitrate, iron gluconate, and potassium permanganate) on water-based drilling fluids (WBDFs). The additives were tested on two actual field drilling mud samples that differ mainly in their weight. The scavengers’ impact on drilling muds was investigated by measuring their scavenging capacity and their effect on rheology, fluid loss, and pH. Potassium permanganate outperformed the other scavengers when added to the lighter (lower density) WBDF. However, it did not impact the scavenging capacity of the heavier mud system. Copper nitrate outperformed the other scavengers in the heavier drilling mud system. Also, the addition of copper nitrate in the lighter mud system increased its H2S-scavenging capacity greatly, while for iron gluconate, it did not perform very well. Overall, all the scavenger-containing drilling muds did not have any significant harmful impact on the plastic viscosity or the fluid loss properties of the drilling muds. Furthermore, all the tested drilling mud samples showed an excellent ability to clean wellbores and suspend drill cuttings evident by the high carrying capacity with the exception of iron gluconate or potassium permanganate with the heavy mud system.

Calcium sulfate (CaSO4) scale has been identified as one of the most common scales contributing to several serious operating problems in oil and gas wells and water injectors. Removing this scale is considered an economically feasible process in most cases as it enhances the productivity of wells and prevents potential severe equipment damage. In this study, a single-step method utilizing potassium carbonate and tetrapotassium ethylenediaminetetraacetate (K4-EDTA) at high temperature (200 °F) has been used to remove CaSO4 scale. The CaSO4 scale was converted to calcium carbonate (CaCO3) and potassium sulfate (K2SO4) using a conversion agent, potassium carbonate (K2CO3), at a high temperature (200 °F) and under various pH conditions. Various parameters were investigated to obtain a dissolver composition at which the optimum dissolution efficiency is achieved including the effect of dissolver pH, soaking time, the concentration of K4-EDTA, the concentration of potassium carbonate (K2CO3), temperature impact and agitation effect. Fourier transform infrared, X-ray crystallography, ion chromatography, stability tests and corrosion tests were carried out to test the end product of the process and showcase the stability of the dissolver at high temperature conditions. A reaction product (K2SO4) was obtained in most of the tests with different quantities and was soluble in both water and HCl. It was observed that the dissolver solution was effective at low pH (7) and resulted in a negligible amount of reaction product with 3 wt% CaSO4 dissolution. The 10.5-pH dissolver was effective in most of the cases and provided highest dissolution efficiency. The reaction product has been characterized and showed it is not corrosive. Both 7-pH and 10.5-pH dissolvers showed high stability at high temperature and minimum corrosion rates. The single step dissolution process showed its effectiveness and could potentially save significant pumping time if implemented in operation.