فهرست مطالب

Iranian Journal of Oil & Gas Science and Technology
Volume:10 Issue: 3, Summer 2021

  • تاریخ انتشار: 1400/07/25
  • تعداد عناوین: 7
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  • Behrouz Bayati *, Mohsen Mansouri, Hossein Hejazi Pages 1-19

    In this study, effect of ethylene vinyl acetate (EVA) as an inhibitor on wax appearance temperature (WAT) of crude oil in the Iranian oil field has been investigated using differential scanning calorimetry (DSC) method. The effect of EVA on the morphology of crude oil wax crystals has been investigated using a system designed to be equipped with an ocular microscope. The EVA inhibitor has a very good performance in reducing the Wax appearance temperature of crude oil and by adsorbing on the growing wax crystals, it prevents the crystallization process and also their connection to each other to form a network structure. By 800 ppm of the EVA inhibitor, the largest decrease occurred in the WAT of crude oil (at the rate of 26.13 ° C) and also smaller crystals and weaker structures were formed at this concentration. Therefore, 800 ppm of EVA inhibitor was selected as an optimal value

    Keywords: Wax Precipitation, DSC, ethylene vinyl acetate inhibitor, morphology, Wax Appearance Temperature
  • Siavash Ashoori *, Ehsan Safavi, Jamshid Moghaddasi, Parvin Kolahkaj Pages 20-38

    Formation damage is being reported during the secondary and tertiary stages of reservoir lifespan. One of the unpleasant sequences of formation damage caused by fine particles is permeability reduction due to pore plugging and bridging. The fine particles might exist initially in a porous medium, or be introduced by the external sources. In addition, there is a variety of particle types and sizes. The current research focuses on the effects of non-swelling clay minerals motions, such as the laminar ones found in Iranian sandstone reservoirs, on permeability. For this purpose, sand packs in a variety of glass bead sizes and containing aluminium oxide as fine particles were designed to scrutinize the motion of fine particles under various pressure differences, flow rates, and fine concentrations. It was concluded that for each of the three sand packs considered as the porous media in this study and composed of fine glass beads with different sizes, there is a critical flow rate which is a function of glass bead size. For the flow rates less than critical flow rate, bridges form stably and lead to the highest formation damage. After reaching the critical flow rate, the bridges weaken and then break; thereafter, relative permeability would be independent of flow rate. All in all, it was deduced that permeability reduction and formation damage are directly proportional to particle concentration, and inversely proportional to glass bead size. The reason for using solid glass spheres in this study is their flow ability, great strength, chemical stability, low thermal expansion. 

    Keywords: Fine migration, Permeability Reduction, Formation Damage, Critical flow rate
  • Temple Chikwe *, Mudiaga Onojake Pages 39-48

    The concentrations of trace metals in crude oil samples obtained from eight producing fields from Niger Delta Nigeria were analyzed using a 700 model Perkin Elmer Atomic Absorption Spectrophotometer. Results showed the following ranges for the trace metals, Cu (0.01- 0.04 mg/kg); Fe (0.05 – 5.90 mg/kg); Ni (0.09 – 0.72 mg/kg); V (0.008 – 1.05 mg/kg). Pb and Zn were < 0.01 mg/kg. Trace metal ratios such as V/Ni; V/Fe and V/V + Ni were used to unravel the genetic correlation among the oils. Results showed that all the crude samples except sample from Nembe South-2 have a V/N ratio < 1 indicating the organic material that produced the petroleum source rock. A cross plot of V/Ni revealed two genetic families for the crude oils, derived from a terrestrial and marine origin. This was confirmed by the Ternary plot of V, Ni and Fe which discriminated the crude oils from the producing fields into two distinct groups. The V/(Ni+V) of < 0.5 shows that most of crude oil were deposited in an oxic environment. A cross-plot of V/(Ni+V) and V/Fe showed a weak correlation which suggests that it cannot be used as a substitute for the V/Ni ratio in determining the origin and depositional environment of crude oil samples. Therefore, in-depth knowledge of the concentration of trace metals especially vanadium and nickel within an environment during oil exploration is very essential in developing new oil locations.

    Keywords: marine, terrestrial, oxic, anoxic, Source rock
  • Nima Hamidian Shoormasti, Seyyedalireza Tabatabaei Nezhad * Pages 49-69

    Prediction of transport parameters is an important issue in shale formations. A unique and novel method to address this subject is the Revil model (Revil et al. 2011) which has been updated here for multivalent salts. The updated model for water and ion transport through shale has been evaluated against a range of experimental data sets. The updated Revil model only needs a few number of shale properties such as cation exchange capacity (CEC), porosity, and grain density which can be readily measured in laboratory. Also in the present work three parameters (f_Q,β_((+))^S,ν) have been considered as calibration parameters in the dynamic mode.In addition to updating Revil model for multivalent salts, we derived equations to calculate water and ion uptake in shale sample, a simplified equation to estimate IS and a proof for the conjecture that IS correlates with ME.The results show that in static mode, the model predicted the trend of data, however, the effect of semipermeable nature of shale on water uptake and alteration of ionic concentration in pore space was found negligible because of high salt concentrations (i.e. Cf>0.5M). In dynamic mode, by adjusting calibration parameters for each of test data, a complete matching could be obtained. In case of adjusting all experiments with only three common calibration parameters the prediction was not satisfactory, however, the results of "intact-anion method" was more accurate than "Donnan method". When multiple sets of ME data in a broader range of concentration including low concentrations were plotted along with high-concentration data, correlativity was significant (R2>0.9). The present study for the first time in petroleum engineering research, suggested and implemented the updated Revil model as an applied tool for investigating static and dynamic behavior of semipermeable shales.

    Keywords: Membrane Efficiency, Ion Selectivity, Updated Revil Model, Donnan Method, Intact-Anion Method
  • Yaser Ahmadi * Pages 69-82

    Using nanoparticles for adsorbing asphaltene was known as one of efficient methods among researchers for upgrading of real oil samples in comparison to other expensive mechanical treatments or even solvents (such as n-pentane and n-heptane) and surfactants. In this study, Nickel zeolite oxide nanoparticles have been used for asphaltene adsorption and solving asphaltene precipitation problems. Although Nickel zeolite oxide nanoparticle used in previous studies as an asphaltene adsorbent, observing relation between asphaltene adsorption on its surface and asphaltene precipitation in the presence of nanoparticles was not covered. Series of experiments include FTIR, CO2-oil IFT tests, Langmuir and Freundlich isotherm models, and natural depletion tests were performed in the presence of Nickel zeolite oxide nanoparticles. Adsorption data was fitted well with the Langmuir model in comparison to the Freundlich model which shows that the adsorption occurs in a homogeneous surface with monolayer coverage. Based on the CO2-oil IFT results, there are two different slope forms in IFT readings as pressure increase from 150 Psi to 1650 Psi. Second slope (900 Psi-1650 Psi) is slower than the first one (150 Psi-900 Psi) which was due to aggregation of asphaltene. Three pressures of 1350 Psi, 1500 Psi, 1650 Psi and Nickel zeolite oxide nanoparticles at concentration of 30 ppm were selected for performing natural depletion tests and the basis of selection was high efficiency of adsorption in these points. As pressure decrease from 1650 Psi to 1350 Psi, asphaltene precipitation changes from 8.25 wt % to 10.52 wt % in the base case and it was 5.17 wt % to 7.54 wt % in the presence of Nickel zeolite oxide 30 ppm. Accordingly, Nickel zeolite oxide nanoparticles adsorbed asphaltene on its surface in proper way and the amount of asphaltene precipitation was decreased in the presence of Nickel zeolite oxide nanoparticles.

    Keywords: CO2-oil IFT tests, Adsorption, Asphaltene, Isotherm models, Nickel zeolite oxide nanoparticles
  • Aref Khazaei, Reza Radfar*, Abbas Toloie Eshlaghy Pages 83-98

    Iran is one of the largest producers of oil and gas in the world. The use of smart manufacturing approaches can lead to better performance and less costs of the well drilling process. One of the most important issues during the drilling operation is the wellbore stability. Instability of wellbore can occur at different stages of a well's life and inflict heavy financial and time damages on companies. Selecting a proper drilling mud weight, which is a controllable factor, can prevent lots of these damages. The main goal of this research is presenting a drilling mud weight estimator for Iranian wells using Deep-learning techniques. Our Iranian dataset only contains 900 samples, but efficient deep models usually needs large amounts of data to obtain acceptable performance. Therefore, the samples of two datasets related to the United Kingdom and Norway fields are also used to extend our dataset. Our final dataset has contained more than half million samples that has been compiled from 132 wells of three fields. Our presented mud weight estimator is an artificial neural network with five hidden layers and 256 nodes in each layer that is able to estimate the mud weight for new wells and depths with the mean absolute error (MAE) of less than ±0.039 pound per gallon (ppg). In this research, the presented model has been challenged in real-world conditions. The results have shown that our model can be reliable and efficient in the real world.

    Keywords: Drilling Mud Weight, Deep-learning, Smart Manufacturing, Artificial Neural Networks, Mean Absolute Error
  • Karim Salahshoor*, Seyed morteza Hoseini Pages 99-116

    Model-based optimization of waterflooding process has found significant scope for improvement of the economic life-cycle performance of oil fields due to geological and economic uncertainties compared to the conventional reactive strategies. A new frequency-based system identification method is proposed in this paper to identify a robust Multi-Input, Multi-Output (MIMO) surrogate model for an oil reservoir under waterflooding process to describe all the injector-producer relationships. In contrast to the conventional modeling methods, the proposed data-driven modeling approach uses the available injection and production rates as reservoir input-output data. Meanwhile, it includes a structured-bounded uncertainty model in the form of norm-bounded state-space function blocks to account for uncertainties. This facilitates the identified model to be employed in robust control methodology using linear matrix inequality (LMI) problem formulation to eliminate the effect of model uncertainty. The identified MIMO surrogate model is integrated with a desired nonlinear net present value (NPV) objective function in a Multi-Input, Single-Output (MISO) system configuration to synthesize a model-based optimization prediction for economic operation and production of oil from oil reservoirs under both geological and economic uncertainties. The introduced approach is implemented on “EGG model” as a well-recognized three-dimensional synthetic oil reservoir with 8 water injection wells and 4 oil production wells. The results clearly demonstrate that economic performance prediction of the oil reservoir, having uncertain permeability field, lies in the evaluated bound of the uncertainty model.

    Keywords: Waterflooding, System identification, Surrogate model, Economic