Recently low-salinity waterflooding was introduced as an effective enhanced-oil-recovery (EOR) method in sandstone and carbonate reservoirs. The recovery mechanisms that use low-salinitywater injection are still debatable. The suggested possible mechanisms are: wettability alteration, interfacial-tension (IFT) reduction, multi-ion exchange, and rock dissolution. In this paper, we introduce a new chemical EOR method for sandstone and carbonate reservoirs that will give better recovery than the low-salinitywater injection without treating or diluting seawater.In this study, we introduce a new chemical EOR method that uses chelating agents such as ethylenediaminetetraacetic acid (EDTA), hydroxyethylethylenediaminetriacetic acid (HEDTA), and diethylenetriaminepentaacetic acid (DTPA) at high pH values. This is the first time for use of chelating agents as standalone EOR fluids. Coreflood experiments, interfacial and surface tensions, and zeta-potential measurements are performed with DTPA, EDTA, and HEDTA chelating agents. The chelating-agent concentrations used in the study were prepared by diluting the initial concentration of 40 wt% with seawater and injecting it into Berea-sandstone and Indiana-limestone cores of a 6-in. length and a 1.5-in. diameter saturated with crude oil. The coreflooding experiments were performed at 100 C and a 1,000-psi backpressure. Low-salinity-water and seawater injections caused damage to the reservoir because of the calcium sulfate scale deposition during the flooding process. The newly introduced EOR method did not cause calcium sulfate precipitation, and the core permeability was not affected. The core permeability was measured after the flooding process, and the final permeability was higher than the initial permeability in the case of chelating-agent injection. The coreflooding effluent was analyzed for cations with the inductively coupled plasma (ICP) spectroscopy to explain the dissolution-recovery mechanism. The effect of iron minerals on the rock-surface charge was investigated through the measurements of zeta potential for different rocks containing different iron minerals.HEDTA and EDTA chelating agents at 5 wt% concentration prepared in seawater were able to recover more than 20% oil from the initial oil in place from sandstone and carbonate cores. ICP measurements supported the rock-dissolution mechanism because the calcium, magnesium, and iron concentrations in the effluent samples were more than those in the injected fluids. The IFTreduction mechanism was confirmed by the low IFT values obtained in the case of chelating agents. The type and concentration of chelating agents affected the IFT value. Higher concentrations yielded lower IFT values because of the increase in carboxylic-group concentration. We found that the high-pH chelating agents increased the negative value of zeta potential, which will change the rock toward more water-wet.
Barium sulfate (barite) is a major oil and gas field scale formed inside the production equipment as well as in the reservoir. During drilling of oil and gas wells, barite serves as a weighting material in different drilling fluid formulations. Barite solubility is very low in inorganic and organic acids. In this study, diethylenetriaminepentaacetic acid (DTPA) chelating agent and a converter (K 2 CO 3 ) are introduced to dissolve barite scale. Potassium carbonate was selected as a converter because it is cheap and available and has no environmental concerns. For the first time, the reaction kinetics of DTPA chelating agent and the converter with intact barite rock samples are investigated. Barite core samples were plugged from actual barite rock that is used to prepare the barite powder for the drilling fluid. The reaction kinetics of DTPA and the converter with barite rocks were studied by a rotating disk apparatus (RDA). The results of the RDA show a linear increase in the reaction rate with the disk rotational speed, suggesting that mass transfer controls the dissolution of barite in DTPA chelating agent. The converter reacts with barite at a high pH medium (pH above 11) and generated barium carbonate. The resulting barium carbonate added more surface area to the disk and increased the diffusion coefficient of DTPA from the bulk solution to the rock surface. Also, the complexation of barium from barium carbonate is much easier than that from barite. The DTPA diffusion coefficient increased from 0.1 × 10 −6 to 3.31 × 10 −6 cm 2 /s as a result of the use of K 2 CO 3 as a converting agent. The evaluation of reaction kinetics between DTPA/converter and the rock will help design more efficient removal for both barite scale and barite filter cake in upstream oil and gas wells.
The equivalent circulation density (ECD) is a very important parameter in drilling high-pressure high-temperature and deepwater wells. ECD is a key parameter during drilling through formations where the margin between the pore pressure and the fracture pressure (FP) is narrow. In these critical formations, the ECD is used to control the formation pressure and prevent kicks. Recent approaches in oilfields to determine ECD depend mainly on using expensive downhole sensors for providing real-time values of ECD. Most of these tools have operational limitations such as high pressure and high temperature which may prevent using these tools in downhole conditions. The objective of this paper is to develop a new approach for predicting ECD using artificial intelligence (AI) techniques from surface drilling parameters [mud weight, drill pipe pressure, and rate of penetration (ROP)]. 2376 data points were used to develop the AI models. The data were collected during the drilling of an 8.5″ vertical hole section. Two AI models were used to estimate the ECD: artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS). An empirical correlation for ECD was derived from the optimized ANN model by extracting the weights and biases. The developed ANN and ANFIS models were able to calculate ECD with a correlation coefficient (R) of 0.99 and average absolute percentage error of 0.22% for ANN and ANFIS models, respectively. The developed empirical correlation for the ANN model can be used during well design to choose a correct mud weight to safely drill the well based on the expected drilling parameters. It will also minimize the drilling problems related to ECD such as losses or gains especially in critical situations where the margin between the pore and fracture pressure is very narrow. In addition, using this technique will save cost and time by reducing the need for expensive, complicated downhole tools.
Iron sulfide scale is a common problem in the oil and gas industry. The precipitation of the iron sulfide scale on the well completion tools or inside surface flow lines restricts the flow of the produced fluids and might affect the integrity of the pipelines or the surface and subsurface tools. Failure of the downhole completions tools will not only reduce the production rates but it might require workover and remedial operations that will add extra cost. The main objective of this paper is to evaluate a new environmentally friendly acid system (NEFAS) for iron sulfide scale removal using an actual field sample. The scale sample collected from a natural gas well is dominated by pyrrhotite (55%) in addition to calcite (21%), pyrite (8%), and torilite (6%) with minor traces of hibbingite, siderite, geothite, akaganeite, and mackinawite. High-temperature solubility tests were performed by soaking 2 g of the scale field sample with 20 cm3 of the NEFAS under static condition at 125 °C for different time periods (2, 6, 12, 18, and 24 h). The solubility results were compared with commercial solutions for iron sulfide scale removal such as hydrochloric acid (15 wt.%), glutamic acid diacetic acid (GLDA, 20 wt.%), and high density converters (HDC-3) under the same conditions. The corrosion test was performed at 125 °C for the developed solution after mixing with 2 wt.% corrosion inhibitor (CI) and 2 wt.% corrosion intensifier (CIN). The results were compared with HCl (15 wt.%) under the same conditions. NEFAS consists of 75 wt.% biodegradable acid at pH of 0.04. NEFAS achieved 83 g/L solubility of iron sulfide scale after 6 h at 125 °C under static conditions. The solubility efficiency was very close to 15 wt.% HCl after 24 h where the solubility was 82 and 83 g/L for NEFAS and HCl, respectability. HDC-3 and GLDA (20 wt.%) achieved a lower scale solubility; 18 g/L and 65 g/L respectively, after 24 h. NEFAS achieved a corrosion rate of 0.211 kg/m2 after adding the CI and and CIN compared to 0.808 kg/m2 for HCl. The new environmentally friendly biodegradable acid system provides efficient performance for the scale removal without harming the environment and causing any side effects to the operation.
The rheological properties of the drilling fluid play a key role in controlling the drilling operation. Knowledge of drilling fluid rheological properties is very crucial for drilling hydraulic calculations required for hole cleaning optimization. Measuring the rheological properties during drilling sometimes is a time-consuming process. Wrong estimation of these properties may lead to many problems, such as pipe sticking, loss of circulation, and/or well control issues. The aforementioned problems increase the non-productive time and the overall cost of the drilling operations. In this paper, the frequent drilling fluid measurements (mud density, Marsh funnel viscosity (MFV), and solid percent) are used to estimate the rheological properties of bentonite spud mud. Artificial neural network (ANN) technique was combined with the self-adaptive differential evolution algorithm (SaDe) to develop an optimum ANN model for each rheological property using 1029 data points. The SaDe helped to optimize the best combination of parameters for the ANN models. For the first time, based on the developed ANN models, empirical equations are extracted for each rheological parameter. The ANN models predicted the rheological properties from the mud density, MFV, and solid percent with high accuracy (average absolute percentage error (AAPE) less than 5% and correlation coefficient higher than 95%). The developed apparent viscosity model was compared with the available models in the literature using the unseen dataset. The SaDe-ANN model outperformed the other models which overestimated the apparent viscosity of the spud drilling fluid. The developed models will help drilling engineers to predict the rheological properties every 15–20 min. This will help to optimize hole cleaning and avoid pipe sticking and loss of circulation where bentonite spud mud is used. No additional equipment or special software is required for applying the new method.
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