مجله ژئومکانیک نفت
سال ششم شماره 3 (Autumn 2023)

Seismic tomography is one of the seismic imaging techniques which are interesting due to the possibility of recording high-frequency seismic waves and providing the possibility of obtaining high-quality images from inside the earth. The ability to record high-frequency waves enables the identification of faults, fractures, and joints with sufficient accuracy, which are very important in reservoir geomechanics studies. In this paper 2D crosswell seismic tomography is simulated by PyGIMLi (python geophysical inversion and modeling library). Crosswell seismic tomography is a routine part of seismic explorations, particularly hydrocarbon exploration. Fast marching and Gauss-Newton methods are the default algorithms for Traveltime forward modeling and inversion, respectively. The fast marching method is a very efficient method for calculating the travel time and path of seismic waves in homogeneous and especially non-homogeneous environments. This method uses the finite difference algorithm to solve the eikonal equation in gridded velocity environments. The Gauss-Newton method is a powerful classic method that can work with all types of geophysical data, which by properly weighting the data and creating a constraint, makes the inversion process faster and more accurate So that the inversion error is below 5% in all cases. The results obtained from the inversion show that the Gauss-Newton method has performed well and the anomalies designed in the models have been correctly detected so that the results can be interpreted without difficulty. Also, changing survey parameters influenced the results of inversion and it was necessary to determine these parameters correctly so that the results of inversion are more accurate and precise. Simulation crosswell seismic tomography is an important step before a successful practical crosswell seismic tomography. In general, simulation before any geophysical survey can be very helpful.

Sand production by eroding downhole and surface equipment, production loss, and some other impacts can greatly increase hydrocarbon recovery and operational costs. Prediction of sand production in oil wells is generally conducted by using linear Darcy’s law as the constitutive equation for oil flow. This simple law does not include the contribution of fluid inertial in pressure drop and therefore is valid when the flow velocity is low. In petroleum engineering, deviation from Darcian trend is ordinarily considered important for gas wells, however in a perforated oil well considerable flow convergence occurs near the perforation tunnels, which makes it susceptible to inertia effects. In this paper, impacts of flow inertia on sand production from vertical cased-and-perforated oil wells are numerically analyzed. In this regard, 3D coupled, poro-elastoplastic finite element methods with arbitrary Lagrangian-Eulerian adaptive mesh approach are employed. Forchheimer’s law is utilized to account for high velocity flow effects in the analysis. A pressure gradient-based erosion law is adapted for use as the sanding criterion. The helical symmetry of the perforations, generally the case in practice, is utilized to achieve a more realistic but efficient simulation. Sanding response modifications due to inertia effects are presented for the considered range of parameters. The results indicate that high velocity flow leads to an increase in hydrodynamic forces around the perforation tunnels, which in turn can lead to more sand production. It is shown that ignoring the effects of inertia in perforated oil wells can lead to significantly lower predictions of both amount and rate of sand production.

Non-coaxiality plays a key role in modelling of problems with significant stress rotation in soil mechanics. This will be more crucial in types of soils or granular materials with anisotropy. Many of the constituent rocks of oil and gas reservoirs are of the anisotropic type, so considering anisotropy in the study of oil reservoirs will have special significance. Neglecting to account for stress and strain non-coaxiality would result in errors and overestimating soil capacity. A mathematical solution is developed and applied within the framework of multi-laminate model, to deal with this issue. Selecting multi-laminate frame as the base of the model facilitates consideration of anisotropy with less mathematical effort. In addition, tracing fabric evolution may be much easier in this framework. Concept of stress and strain vector fields are introduced for shear components of planes, and in contrast to ancestor multi-laminate models, shear stress is calculated through this concept for each plane in the proposed model. Using this method, non-coaxiality may be considered on planes, and consequently the integrated result of plane stresses will be non-coaxial as well. Finally, to apply the model for greater problems, a code is developed to introduce the new model to FE program, Opensees. The program is implemented for analyzing an experimental plane-strain loading test of an anisotropic dense specimen of Toyoura sand. The results show a good agreement between theory and experiment.

Crack propagation in the low permeable reservoir rock as an explosive fracturing technique can be used to increase the permeability and productivity of unconventional reservoirs. This technique is the same as hydraulic fracturing but uses blast-induced shock waves and gas pressure to generate and propagate radial cracks around the wellbore in a particular reservoir. In this study, we want to simulate the explosion-induced crack initiation and propagation around a wellbore as a stimulation method of unconventional reservoirs using an analytical-numerical technique. Therefore, the dynamic crack initiation and propagation process of deep rock caused by the explosion is considered both analytically and numerically. The mechanical process of rock cracking under the action of an explosion stress wave is theoretically analyzed and simulated with a finite difference method. Then the coupling effect of explosion load in the form of shock wave and gas pressure is established numerically based on the two-dimensional explicit finite difference and displacement discontinuity methods, respectively. The analytical method involved the solution of the Lame-Navier equation in elasto-dynamics based on the Green’s function solution. The simulation procedure consists of coupling the explicit finite difference method with the displacement discontinuity method in the form of higher-order displacement discontinuities along the boundaries of the problem. All of the mentioned processes have been done in an oil field with a density of 2.5 gr/cm3, Poisson’s ratio of 0.2, and elastic modulus of 20 GPa. The numerical results of this research show that shock waves are responsible for the initiation and propagation of radial cracks around the wellbore which in turn is filled with pressurized gas due to explosion. Then, these shock wave-induced radial cracks are propagating in the reservoir rock because of the explosive gas pressure inside them. This rock fracturing mechanism can help to improve the permeability and productivity of the highly low-permeable reservoirs in horizontal wells.

The infiltration of crude oil and its derivatives into the soil leads to changes in the mechanical behavior of the soil in addition to detrimental and environmental problems. This study aims to evaluate the bearing capacity of geocell-reinforced strip footings laid on oil-contaminated sand under eccentric load via numerical modeling using PLAXIS 2D. The behavior of the footing is assessed regarding various oil contents of 0, 3, 6, 9, and 12% under loading with different eccentricities of e/B=0, 1/12, 1/6, and 1/3. Numerical results revealed that soil pollution has a negative effect on the performance of strip footings, so that an increase in oil content led to a reduction in the magnitude of the load capacity. It was observed that reinforcement with geocell increases the bearing capacity of footing located on the oil-contaminated medium under different eccentricities. The effect of reinforcing with geocell was higher for contaminated soil compared to clean one. Further, the load capacity improvement factor (IF) increased by increasing oil content and settlement value. The results revealed that the reinforcing effect increased with an increase in load eccentricity for both clean and contaminated soils. In addition, the use of geocells is most effective when the loading is outside the core of the foundation, i.e., e/B>1/6. The footing tilting around the centerline axis of the footing due to load eccentricity as well as soil reinforcement with geocell led to a reduction in the stress-affected zone and as a result the displacement depth of the soil beneath the foundation.

Optimizing reservoir performance in fractured reservoirs relies heavily on understanding and harnessing fracture connectivity at the reservoir scale. Voroni triangulation Discrete Fracture Network (DFN) models offer a unique depiction of fractures and their connectivity compared to other methods. Petrophysical property modeling involves various algorithms, with DFN emerging as a novel mathematical approach. This study centers on a segment of Khangiran's hydrocarbon formations, analyzing reservoir porosity and permeability. Among the plethora of available methods, fractal geometry, particularly through the box counting method, proves apt for estimating these properties. By increasing the box size to explore point distribution in the background space, the method calculates fractal dimensions, aiding in porosity and permeability estimation. Applied in modeling, this technique presents a new ellipsoid-based prediction model, providing a comprehensive description of petrophysical properties in reservoir-prone areas. The results, aligned with geological features, mud loss data, and production outcomes, demonstrate remarkable compatibility with lower uncertainty, presenting a promising avenue for enhanced reservoir characterization and performance optimization. The three-dimensional block model estimations derived from the Integrated Discrete Fracture Network (DFN) algorithm with a fractal dimension of complex sequences distribution align with well test analysis and production data results. The iterative application and refinement of the DFN algorithm and fractal dimension modeling process hold potential for further enhancement across the Khangiran reservoir or other hydrocarbon fields. The findings indicate that well 11 is optimally configured and likely exhibits superior performance in terms of hydrocarbon production within the reservoir.