مجله ژئومکانیک نفت
سال یکم شماره 2 (پاییز و زمستان 1396)

Summary Hydraulic fracturing (HF) is one of the most important technologies ever developed by the oil industry. In this paper, a hydraulic fracture job is designed for Hugoton gas field in a relatively low permeability sandstone in a vertical well. A step by step procedure is introduced and followed to determine stresses, pressures, proper proppant selection, fluid loss volume, required volume of fracturing fluid, pumping duration and rates, geometry of the expected hydraulic fracture and job efficiency. The HF design is compared with numerical results which showed a good agreement. Based on the design parameters it is expected an HF half-length of 500 ft. height of 173 ft. could be achieved at the end of the treatment. Introduction Hydraulic fracturing is a widespread technology used in oil industry to enhance the production. The technology has given the opportunity the produce from many previously un-economic reservoirs. Unlike drilling technology which has been extensively developed in the past decades, most HF technology development was achieved in 1950s and 1960s. The developed design of HF can still be an important part of an HF design without the need of advanced numerical modeling. The classic HF design uses some simplifications that may reduce the accuracy of the method. This shortcoming may be overcame by complementary numerical modeling. However, the classic design is still an essential part of an HF design. Methodology and Approaches The first step in an HF design is determining in-situ stresses and pressures and making sure of their accuracy and reliability. The in-situ stresses were estimated based on empirical gradients. Then the results were calibrated by several well tests such as SRT, DFIT, etc. These tests’ results were also used to calibrate other inputs including pore pressure, lost circulation coefficient etc. An appropriate proppant type was selected based on the required permeability and the cost of the proppant. Results and Conclusions A complete schedule for HF job including injection volume, pump rate, Pad stage volume, proppant usage and fluid efficiency was designed and presented. Based on the design, a hydraulic fracture half-length of 500 ft. with 173 ft. height was expected. Comparison of results of a fully 3D numerical model (with similar input variables, already available from previous studies) and a P3D model (with exact input parameters) with expected design results showed a good agreement. The propagated fracture length and height and also proppant distribution in fractures of the numerical model are in agreement with the expected results. The design procedure proposed in this paper may be used as a guideline for a successful HF design of vertical wells.

Drillability of rock is defined in terms of a large number of parameters. However, in most drilling rate models uniaxial compressive strength (UCS) was used as rock drillability. There is a paucity of researches to combine rock drillability with the penetration rate model. Thus, in this study, rock drillability will be calculated based on the penetration rate. BYM was chosen as drilling rate mathematical model to normalize the penetration rate into operational parameters. After eliminating effects of drilling parameters, regression method will be used to evaluate relationships of rock paramters (such as Confined Compressive Strength (CCS), UCS, porosity, clay content, density, Poisson’s ratio, and internal friction angle) with drilling rate. Then, the best parameters of rock based on determination of coefficient will be selected to compute rock drillability. To define coefficients of this model, multiple non-linear regression will be used. The comparison between the modified version of BYM with rock dirllability index and the prior BYM will be done to validate the proposed method. For this research data were gathered from one vertical well in Karanj oilfield. Results indicated that rock parameters significantly affect the penetration rate. Evaluating relationships of understudied rock parameters with drilling rate revealed that UCS, CCS, porosity and shale content have high determination coefficients. The comparison between modified BYM and original BYM showed that applying computed rock drillability using three rock parameters (i.e. CCS, friction angle, density and Poisson’s ratio clay content) in BYM improves accuracy of prediction.

the porous media of oil reservoirs have different layers with wide range scales which are different from effective scale of fluid flow in reservoirs. To reduce the calculating time of porous reservoirs modeling, each physical effect should be treated separately on its scale and area of influence. In this paper, the capillary pressures parameters between fluid phases were added on a multiscale deformable model to increase the accuracy of modeling. So, the governing equation was revised and a homogeneous oil reservoir was analyzed considering capillary influences. Comparing the results of analyzing the homogeneous oil reservoir with or without capillary effect shows that the water pressure was increased around the injection point and was decreased around the production point after considering capillary. It seems that the effects of capillary pressures on fluid pressures was significant and should be considered especially in modeling of inhomogeneous reservoirs due to increasing the irregularity flowing.

One of the main objectives of 4D seismic interpretations is to estimate pressure and saturation change caused by reservoir production and injection. Estimation of these changes would assist to update the simulation and geomechanical models of our hydrocarbon reservoirs. Different techniques have been recently proposed to estimate the pressure and saturation changes using 4D seismic data. Typically, these methods linearly decompose the effect of pressure and saturation changes. For calibration of the proposed equations, laboratory measurements, rock physics relationships or even reservoir scale simulation model and well production data have been employed. Although, they work reasonably well in the given datasets, there is a need for extensive pre-setting steps to calibrate these equations which in turns requires time and cost. In this paper, Rock Physics and Petrophysics principles are utilised in order to develop two independent attributes which can calculate the pressure and saturation changes, separately. Both equations are easy to apply and interpret, and require not more than a few hours for their parameters calibration. Although, these two independent attributes were successfully implemented in one of the North Sea complex oil reservoir, but both attributes are qualitative indication of pressure and saturation changes.

In this paper, we begin with a discussion on the relations between seismic velocity and porosity in clastic reservoirs. We then provide a brief overview of the theoretical background for some important rock physics models in granular media, including friable-sand model, contact-cement model and constant-cement model. We then present an example of application of rock physics modeling to a well log and core dataset extracted from a real case study. Based on a rock physics diagnostic technique, it is possible to quantify different diagenetic and sedimentologic factors in terms of rock physical properties. In this study, on a real dataset, this is carried out by adjusting the curve of a rock physics theoretical model (constant-cement model) to a trend in the velocity–porosity dataset, and then interpreting the rock physics/microstructure as that used in the theoretical model. This model is then used to make prediction of seismic velocities. The results of this study can be used to interpret the seismic data quantitatively and update the reservoir property models.

Seismic wave velocity along with petrophysical data provide valuable information at the exploration and development phases of oil and gas fields. The compressional-wave velocity (Vp) is acquired using conventional acoustic logging tools in many drilled well. But the shear-wave velocity (Vs) is recorded using advanced logging tools only in limited number of wells, mainly because of the high operational costs. So, alternative methods are often used to estimate Vs. Heretofore, several empirical correlations which predict Vs by using well logging measurements and petrophysical data are proposed. But these empirical relations can only be used in limited cases. The use of intelligent systems is an efficient approach for predicting Vs. In this study, in addition to the modified Greenberg-Castagna method, we used the teaching-learning based optimization (TLBO) algorithm to make linear and nonlinear models for predicting Vs. This algorithm is used to make prediction in a sandstone formation from an offshore oil field located at Western Australia and a carbonate formation from an onshore oil filed located at south west of Iran. We compared the estimated Vs values using TLBO algorithm with observed Vs and also with those predicted by modified Greenberg-Castagna relation. The results are showing the algorithm efficiency. The results of linear and nonlinear models are also very close together, but the difference is that the linear model is faster than the nonlinear model and is preferred for predicting Vs. Using the linear model shows that for the sandstone formation the error percent is 2.3 and the regression coefficient is 0.82 and these values are 3.3 percent and 0.95 for the carbonate formation respectively. These values show that the linear model of TLBO algorithm can be used as an efficient way to predict Vs.