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Petroleum Science and Technology - Volume:12 Issue: 1, Winter 2022

Journal of Petroleum Science and Technology
Volume:12 Issue: 1, Winter 2022

  • تاریخ انتشار: 1401/09/29
  • تعداد عناوین: 6
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  • Pooria Kianoush, Ghodratollah Mohammadi *, Seyed Aliakbar Hosseini, Nasser Keshavarz Faraj Khah, Peyman Afzal Pages 2-20
    Accurate knowledge of pore and fracture pressures is essential for drilling wells safely with the desired mud weight. By definition, overpressure occurs when the pore pressure is higher than the normal hydrostatic pressure and is associated with specific environmental conditions in a particular part of the earth. This study focuses on the formation pressure studies’ domain for an oilfield in SW Iran. It generally consists of carbonate rocks with no shale interbeds except for the Kazhdumi Formation. This study is based on information from 23 wells and the interpretation of seismic data. The effective, pore, and fracture pressure models are determined from combined geostatistical models and compared with fractal models. The highest correlation between the final effective pressure cube and the velocity cube is related to the lower Fahliyan Formation with 86% and Ilam with 71%, which indicates the accuracy of the modeled data with the original data. Based on the final formation pressure cubes, the maximum pore pressure is 10,000 psi in the Gadvan Formation up to the upper Fahliyan Formation, and the maximum fracture pressure is 13,000 psi in the lower Fahliyan up to the Gotnia Formation. Based on the Logratio matrix obtained from the pressure-volume (P-V) fractal model, the maximum overall accuracy (OA) in the dominant limestone intervals is 0.74 at depths of 2000-3000 meters, which is related to the Asmari to Sarvak Formations. Furthermore, it indicates a high correlation of the pore pressure cube model obtained from the combination of sequential Gaussian simulation (SGS) and co-kriging models with acoustic impedance inversion (AI) for minimizing the time and cost of drilling in new wells of the studied field.
    Keywords: Seismic velocity model, sequential gaussian simulation, formation pressure cube, pressure-volume (P-V) fractal model, Logratio matrix
  • Mahdi Nazari Sarem, Arash Ebrahimabadi * Pages 21-35
    Field experience shows that the cutting transportation and hole-cleaning phenomena are essential during the drilling phase. Particularly in directional drilling, when the accumulation of cutting has caused some drilling problems such as drill string sticking, formation failure, slow rate of penetration, drill bit abrasion, and the like. Through the study, a novel method for efficient hole cleaning, considering different parameters such as flow rate, the drill bit nozzles’ flow area, the consistency and flow behavior indices in the same time using PSO and ACO algorithms were implemented. Moreover, Power Law has been considered for the fluid rheology model. Based on this, the research parameter shows that the PSO algorithm is much more accurate than the ACO algorithm, improving objective function by 50% and 4%, respectively. The performance of each algorithm was evaluated, and the results show that hole cleaning has been significantly improved. The flow rate and the bit nozzle size, which play key roles, were selected as optimization variables. Effective parameters on hole cleaning were evaluated, and the results before and after optimization showed a significant improvement in the model. The PSO and ACO algorithms have been coded in MATLAB software, and the results are compared to the results of the ant colony. The amount of PV and YP has an inverse effect on the increment of minimum velocity required for cutting transport. Various model analyses reveal that the PSO algorithm is more accurate and robust than the Ant colony algorithm.
    Keywords: Optimization, Hole Cleaning, Cutting Bed Height, PSO Algorithm, Ant Colony Algorithm
  • Yicheng Sun *, Zhenglian Liu, Xu Song Pages 36-41
    Kuqa piedmont is the main battlefield of natural gas production in the oil field and the source of west-east gas transmission. The wellbore quality is related to the safety of well construction and production. However, the well cementation quality of the piedmont salt layer is affected by the narrow density window, low casing center degree, and narrow annular gap. Moreover, the qualified rate of well cementation has only been around 50% for many years, which seriously threatens the integrity and safety of the wellbore. Although wildcatters have conducted a series of technical research and practical exploration for many years, the actual application effect is not good. The problem of the inferior well cementation qualitied ratio in the gypsum salt layer is still prominent. Because of the above objective problems and technical limitations, this paper deeply analyzes the influencing factors of the well cementation, which has the qualitied ratio of the gypsum salt layer in the piedmont structure. Based on the three basic points of (1) casing running, (2) column centering, and (3) cementation leakage prevention, this paper studies and applies the combination cementation technology of reaming technology, coupled casing, and fine pressure control, aiming to provide new guidance for the development of the cementation operation of gypsum salt layer, the results of quality improvement and efficiency are remarkable.
    Keywords: Gypsum salt layer, Combined cementation, Cementation quality, Fine pressure control
  • Hoda Yari, Majid Nabi-Bidhendi *, Naser Keshavarz, Reza Heidari Pages 42-51
    Due to the substantial effect of the gas hydrate distribution model (cement, un-cement, or hybrid of both models) on the elastic properties (such as shear modulus, bulk modulus, Poisson’s ratio, etc.), determining the distribution model in the hydrate-bearing sediments is a requirement for decreasing uncertainty in quantitative studies based on seismic velocities. Many different empirical and theoretical rock physics theories cover different ranges of rock properties. Among them, the Effective Medium Theory (EMT) is the most appropriate in quantitative studies of gas hydrate resources. Four types of hydrate distributions have been considered and divided into two cemented and un-cemented categories. EMT is one of the advanced rock physics modeling tools. This theory has been modified by introducing hybrid distribution models of gas hydrate instead of having assumptions about single models of hydrate distribution. Moreover, when a scientific manuscript is written, using dangling and misplaced modifiers are not suggested. On the other hand, one method to determine the gas hydrate distribution model can be performed by identifying AVO’s class on the bottom simulating reflector (BSR); caused by the contrast between an overlying gas hydrate and underlying free gas sediments. This reflector mimics seafloor topography, cross-cuts stratigraphic reflections, and is controlled by thermodynamic conditions. The results of this study on conceptual models showed that in hybrid approach for hydrate distribution, AVO’s class on BSR shows sensitivity to (1) the combination type of gas hydrate distributions models, (2) the total saturation of the gas hydrate and free-gas across the BSR.
    Keywords: Gas hydrate distribution, Effective Medium Theory (EMT), hybrid models, Amplitude Variation vs Offset (AVO)
  • Sara Shokrollahzadeh Behbahani, Mohsen Masihi *, MohammadHossein Ghazanfari Pages 52-61

    In waterflooding process, the time for breakthrough of injecting fluid into a production well is of great importance. Predicting this time helps in designing reservoir development plan. Due to uncertainties in reservoir characterization, estimating the breakthrough is not easy, so alternative methods to estimate quickly the breakthrough time is useful. The percolation method uses limited available reservoir data to predict the breakthrough time distribution, and it may be used for engineering applications. However, implementation of this to real reservoirs requires some adjustments. The aim of this study is to show how percolation approach can be used to real problems. In particular, the effects of permeability contrast between the reservoir and non-reservoir parts in the model are investigated. In order to use the breakthrough scaling function to more realistic reservoir models, a dimensionless breakthrough time was used. The analysis of the breakthrough time of models with zero permeability background (tk=0) and such time for the case of non-zero permeability background (tk=αk) shows a linear dependency which can be used to find breakthrough time distribution. Hence, this correction extends the applicability of the percolation method for predicting breakthrough time when permeability of the system background is not zero.

    Keywords: Porous medium, Percolation theory, Breakthrough time, non zero permeability, permeability contrast
  • Reza Hoveyzavi, Majid Nabi-Bidhendi, Ali Kadkhodaie *, Shahin Parchekhari Pages 62-74
    Logarithmic Mean of Transverse relaxation time (T2LM) and total porosity of the Combinable Magnetic Resonance tool (TCMR) are the main parameters of the Nuclear Magnetic Resonance (NMR) log which provide very substantial information for reservoir evaluation and characterization.  Reservoir properties, for example, porosity and permeability, free and bound fluid volumes, and clay-bound water, could be calculated through the interpretation of T2LM and TCMR. In this manuscript, an intelligent approach has been used by us to predict NMR log parameters and their corresponding electrofacies from well log data. We define NMR electrofacies as classes of NMR log parameters representing reservoir quality are defined by us. For this purpose, NMR logs and petrophysical data are available for two different formations situated in the Ahvaz field. Data from Ilam formation were applied in order to construct the intelligent models, the same as Asmari formation, data were applied for reliability evaluation of the created models.  The outcome results reveal higher performance levels of the Neural Network (NN) technique compared to the neuro-fuzzy (NF) model. The synthetically generated T2LM and TCMR logs are then calculated for the four logged wells from the Ahvaz oilfield using a mathematical function, and they are named Virtual Nuclear Magnetic Resonance (VNMR) logs. Finally, VNMR logs were classified into a set of reservoir electrofacies by cluster analysis approach.  Correlations between the VNMR electrofacies and reservoir quality based on porosity and permeability data helped evaluate the reservoir quality quickly, cost-effectively, and accurately.
    Keywords: Virtual NMR log, neural network, neuro-fuzzy, Back Propagation, Conventional Logs, NMR log parameters, Electrofacies