Iranian Journal of Oil & Gas Science and Technology
Volume:9 Issue: 4, Autumn 2020

Modelling involves the use of statistical techniques or analogy data to infill the inter-well volume producing images of the subsurface. Integration of available data sets from “KO” field were used to identify hydrocarbon prospects and by means of interpolation, populate the facies and petrophysical distribution across the field to define the reservoir properties for regions with missing logging data[KO1] . 3D seismic data, check-shot data, and a series of well logs of four wells were analyzed, and the analysis of the well logs was performed using the well data. The synthetic seismogram produced from the well ties [M.N.2] [KO3] was used to map horizon slices across the reservoir regions. Four horizons and fifteen faults, including one growth fault, four major faults, and other minor faults, all in the time domain were mapped. Attribute analyses were carried out, and a 3D static model comprised of the data from the isochore maps, faults, horizons, seismic attributes, and the various logs generated was built. A stochastic method was also employed in populating the facies and petrophysical models. Two hydrocarbon-bearing sands (reservoirs S1 and S2) with depth values ranging from –1729 to 1929 m were mapped. The petrophysical analysis gave porosity values ranging from 0.18 to 0.24 across the reservoirs, and the permeability values ranged from 2790 to 5651 mD. The water saturation (Sw) of the reservoirs had an average value of 50% in reservoir S1 and 47% in reservoir S2. The depth structure maps generated showed an anticlinal structure in the center of the surfaces, and the mapped faults with the four wells were located in the anticlinal structure. The reserve estimate for the stock tank oil initially in place (STOIIP) of the reservoirs was about 70 mmbbl, and the gas initially in place (GIIP) of the reservoirs ranged from 26714 to 63294 mmcf. The result of the petrophysical analysis revealed the presence of hydrocarbon at favorable quantities in the wells, while the model showed the distribution of these petrophysical parameters across the reservoirs.   Modelling involves the use of statistical techniques or analogy data to infill the inter-well volume producing images of the subsurface. Integration of available data sets from “KO” field were used to identify hydrocarbon prospects and by means of interpolation, populate the facies and petrophysical distribution across the field to define the reservoir properties for regions with missing logging data[KO1] . 3D seismic data, check-shot data, and a series of well logs of four wells were analyzed, and the analysis of the well logs was performed using the well data. The synthetic seismogram produced from the well ties [M.N.2] [KO3] was used to map horizon slices across the reservoir regions. Four horizons and fifteen faults, including one growth fault, four major faults, and other minor faults, all in the time domain were mapped. Attribute analyses were carried out, and a 3D static model comprised of the data from the isochore maps, faults, horizons, seismic attributes, and the various logs generated was built. A stochastic method was also employed in populating the facies and petrophysical models. Two hydrocarbon-bearing sands (reservoirs S1 and S2) with depth values ranging from –1729 to 1929 m were mapped. The petrophysical analysis gave porosity values ranging from 0.18 to 0.24 across the reservoirs, and the permeability values ranged from 2790 to 5651 mD. The water saturation (Sw) of the reservoirs had an average value of 50% in reservoir S1 and 47% in reservoir S2. The depth structure maps generated showed an anticlinal structure in the center of the surfaces, and the mapped faults with the four wells were located in the anticlinal structure. The reserve estimate for the stock tank oil initially in place (STOIIP) of the reservoirs was about 70 mmbbl, and the gas initially in place (GIIP) of the reservoirs ranged from 26714 to 63294 mmcf. The result of the petrophysical analysis revealed the presence of hydrocarbon at favorable quantities in the wells, while the model showed the distribution of these petrophysical parameters across the reservoirs.  [KO1]Sentence has been rephrased.  [M.N.2]This verb does not make sense in this context and has made the sentence unclear.  [KO3]Sentence has been rephrased

The determination of rock types for petrophysical studies has a wide range of applications. It is widely used in drilling, production, and especially in the study and characterization of reservoirs. Zoning of flow units and permeability estimation is one of the challenging tasks of reservoir studies, which uses the integration of data from well logs and analysis of the core. In this study, a Bayesian theory-based statistical modeling method is proposed to identify hydraulic flow units in coreless wells using the concept of hydraulic flow unit and then permeability estimation. In the flow zone indicator (FZI) method, the formation is divided into five hydraulic flow units. In the Winland R35 ethod, however, it is divided into four hydraulic flow units. The Bayesian statistical model divides the existing complex carbonate reservoir rock data into three hydraulic flow units with the most probability of similarity. The second and third hydraulic flow units have closer properties compared to the first hydraulic unit. The Bayesian method-based permeability estimation modeling has acceptable precision, and validation of its results with core data indicates a precision factor of 0.96. The findings of this study can help in better understanding of the concept of flow units and more effective estimation of the permeability of the rocks of the heterogeneous carbonate reservoir.

Ultrasonic irradiation is a new, economic, and environmentally friendly technique for treating asphaltene aggregation in petroleum industry. In this study, the effect of ultrasonic radiation on asphaltene formation is investigated using conventional optical microscopy, viscosity measurement, and Fourier-transform infrared spectroscopy (FTIR). To this end, five crude oil samples, collected from different reservoirs, are used, and the effect of ultrasonic radiation on the structure of the crude oils is investigated at various exposure times. The results show that, at an optimum radiation time, the ultrasonic waves can break the asphaltene clusters and shift the size distribution of the asphaltene aggregate to a smaller size. In addition, the FTIR analysis reveals structural changes in the composition of the crude oil after the ultrasonic irradiation. By increasing the ultrasound exposure time, the viscosity of the asphaltenic oil first decreases to a minimum before rising again. Moreover, the measurement of asphaltene and resin content of the crude oils indicates that at exposure times longer than the one leading to the minimum viscosity, resin molecules are broken upon exposure to ultrasound. This can be the main reason for the existence of an optimum time in the application of ultrasonic radiation, after which the percentage of asphaltene particles and the viscosity of the crude oils increase.

Enhanced oil recovery (EOR) is a vital part of the process of oil production from sandstone and carbonate reservoirs. Maintaining and increasing oil production from many fields require proper selection, design, and implementation of EOR methods. The selection of EOR methods for specific reservoir conditions is one of the most difficult tasks for oil and gas companies. Screening of different EOR techniques considering previous experiences from the methods applied in other fields is a first step in the recommendation of any costly EOR operations. In this paper, EORgui software was utilized to screen eight enhanced oil recovery methods in one of Iran’s offshore sandstone oil fields. The reservoir is composed of two sections with different fluid properties, namely API, viscosity, and oil composition, but relatively homogeneous rock properties and high permeability (1500 mD). The results show that polymer flooding is technically the most suitable enhanced oil recovery method in the upper zone of the reservoir with a high percentage matching score of 90%, and immiscible gas injection with a matching score of 83% is ranked second. For the lower part of the reservoir containing a fluid with much higher viscosity, immiscible gas injection (83% matching) can be recommended. Furthermore, polymer flooding predictive module (PFPM) was utilized to investigate the impact of polymer concentration on oil recovery performance of the upper part with an ultimate recovery of about 40% at the optimum concentration.

Seismic well tying is a crucial part of the interpretation phase in exploration seismology. Tying wells usually involves forward modeling a synthetic seismogram from sonic and density logs and then matching the obtained synthetic seismogram to the seismic reflection data. A huge amount of time is required to deal with it, yet the outcome signal may not be satisfying and may be suffering a low cross correlation between the seismic signal and the synthetic one; it also requires a high quality synthetic trace. Another problem with the so-called manual tying is that the tying process is not repeatable, indicating that one can rarely obtain the same stretched and squeezed signal if the tying procedure is repeated. In recent years, some researchers have used the dynamic time warping (DTW) method to address well tying problems. They have obtained good results according to the correlation between the seismic signal and the warped synthetic signal. This research demonstrates that the result will be better if filtering is applied before tying, and then the warped signal is smoothed. We also propose a simpler algorithm for extracting a warped signal from the warping curve and the original synthetic trace, which gives rise to better performance for well tying.

Today, one of the challenging issues all over the world is the appropriate use of flare gases in oil, gas, and petrochemical industries. Burning flare gases having high heating value results in economic losses and the pollution of the environment. There are several methods to use flare gases; the heat and power generation, the production of valuable fuels, or the separation of more precious components are examples of these methods. In this study, a polygeneration system is designed and simulated for the coproduction of power, steam, methanol, H2, and CO2 from the flare gases in South Pars and Assaluyeh gas fields. The polygeneration system has advantages such as reducing greenhouse gases and the coproduction and sales of energy-related products. The polygeneration system for converting flare gases to energy and various products includes an acid gas removal unit, a synthesis gas production unit, a methanol synthesis unit, a hydrogen purification unit, a combined heat and power generation unit, and a CO2 capture unit. The purpose of this study is to conduct an economic evaluation of the polygeneration system and obtain the total capital cost, the operating profit, and the payback period of this process. The simulation results show that using 9690 kg/h of flare gases produces 8133 kg/h methanol, 653.7 kg/h hydrogen, 46950 kg/h nitrogen, 9103 kg/h CO2, 109850 kg/h medium-pressure steam, and 3.7 MW power. The economic evaluation results show that in the polygeneration system, the total raw material cost and the total utilities consumption cost are $193.8 and $1859.5 per hour respectively, and the total product sales and the total utility sales are $12941.8 and $2243.5 per hour respectively; also, the operating profit is $13132 per hour. Also, the equipment cost, the installation cost, the total capital cost, and the total operating cost are $29.7 million per year, $39.2 million per year, $71 million per year, and $27.9 million per year respectively; finally, the payback period is 1.5 years.

The separation of naphthenic acids from crude oil is difficult, and the presence of such materials in crude oil reduces its value. In this work, using catalytic esterification with methanol, naphthenic acids of crude oil were removed to reduce their harmful effects. SnO2/γ-Al2O3 nanocatalyst was synthesized and used to convert naphthenic acids of crude oil in a fixed bed catalytic reactor. The nanocatalyst was characterized by the X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), and Brunauer–Emmett–Teller (BET) surface area techniques. The XRD revealed the formation of rutile SnO2 on alumina, and the FESEM approved that the catalyst is comprised of nanoparticles with a diameter in the range of 50 to 90 nm. The BET indicated that the catalyst has a mesopore structure with a surface area of 213.4 m2·g–1. The optimal conditions for the catalytic esterification process of naphthenic oil were determined. The temperature of the reduction of the total acid number (TAN) of crude oil ranged from 250 to 360 °C, and the TAN was reduced to less than 0.5 mg KOH/g in this temperature range. A methanol-to-oil ratio (M/O) of 2 wt %, a velocity space of 2.5 h–1, a reaction temperature of 300 °C, and atmospheric pressure were selected as the optimal conditions for the removal of naphthenic acids. Under these conditions, 83% of naphthenic acids was removed. The study indicated that SnO2/γ-Al2O3 could be a promising nanocatalyst for the reduction of total acid of crude oil under mild conditions.