With respect to brittleness, it is about the type of material and its related strength. In comparison with ductile material under load, brittle material has a relatively shorter plastic deformation and responds dominantly by the elastic deformation. With respect to fracability, it is about the rock failure under the ultimate rock strength in either brittle or ductile formation. In comparison, the higher fracable formation should have smaller formation strength than that of the lower fracable formation. In consequence, it is not certain that the brittle formation is easy to fracture than the ductile formation since brittle formation may have greater strength than ductile formation even though the exceptions may exist.

More complications arise when evaluating the responses of subsurface formation in great depth to the formation types (e.g. brittle formation or ductile formation). Under this condition, the impact of confinement on the fracability cannot be ignored. In general, the formation subject to higher confinement pressure is more difficult to fracture as the formation strength is greater. Conversely, the formation subject to lower confinement pressure is easy to fracture since the formation strength is smaller.

In view of efficient stimulation of tight shale gas reservoirs, it is unclear whether we would choose the brittle interval or the ductile interval to fracture as the strength of either interval is unknown. However, it is apparent that we should choose the formation interval with a higher fracability which is equivalent to the lower formation strength. Under the similar confinements, the lower formation strength may be indicated by the smaller unconfined compressive strength (UCS). As a result, it is advisable that the most fracable interval is the one with lowest UCS.

When evaluating the present technology, the formation brittleness should no longer be the associated subject matter as we are unclear about its role to improve the fracability of the tight formation. Disassociating the brittleness with the fracability enables us to focus on identifying the true mechanisms of efficient fracturing of tight shale gas reservoirs.

With the objective review and sensible definition of brittleness used in the present petro-physical field to identify the desirable fracturing intervals, the paper presents the ambiguities of using the brittleness to define the formation fracability and points out that the formation brittleness can be unrelated to the formation fracability. As an alternative approach, the paper provides an effective method to define the most fracable formation intervals in designing the hydraulic fracturing in tight shale gas formations.

Currently, the three-dimensional distribution of interlayer is realized by stochastic modeling. Traditionally, the three-dimensional geological modeling controlled by sedimentary facies models is built on the basis of logging interpretation parameters and geophysical information. Because of shallow gas-cap, the quality of three-dimensional seismic data vertical resolution in research area cannot meet the interlayer research that is below ten meters. Moreover, sedimentary facies cannot commendably reveal interlayer distribution and the well density is very sparse in research area. So, it is difficult for conventional technology to finely describe interlayers. In this document, it uses L₁-L₂ combined norm constrained inversion to enhance the recognition capability of interlayer in seismic profile and improve the signal to noise ratio, the wave group characteristics and the vertical resolution of three-dimensional data and classifies petrophysical facies of interlayer based on core, sedimentary facies and logging interpretation. The interlayer model which is based on seismic inversion model and petrophysical facies can precisely simulate the distribution of reservoir and interlayer. The results show that the simulation results of this new methodology are consistent with the dynamic production perfectly which provide a better basis for producing and mining remaining oil and a new interlayer modeling method for sparse well density.

The main function of traditional proppants is to provide and maintain conductive fractures during well production where proppants should meet closure stress requirement and show resistance to diagenesis under downhole conditions. Many different proppants have been developed in the oil & gas industry, with various types, sizes, shapes, and applications. While most proppants are simply made of silica or ceramics, advanced proppants like ultra-lightweight proppant is also desirable since it reduces proppant settling and requires low viscosity fluids to transport. Additionally, multifunctional proppants may be used as a crude way to detect hydraulic fracture geometry or as matrices to slowly release downhole chemical additives, besides their basic function of maintaining conductive hydraulic fractures. Different from the conventional approach where proppant is pumped downhole in frac fluids, a revolutionary way to generate in-situ spherical proppants has been reported recently. This paper presents a comprehensive review of over 100 papers published in the past several decades on the subject. The objectives of this review study are to provide an overview of current proppant technologies, including different types, compositions, and shapes of proppants, new technologies to pump and organize proppants downhole such as channel fracturing, and also in-situ proppant generation. Finally, the paper sheds light on the current challenges and emphasizes needs for new proppant development for unconventional resources.

There are various types of oils in distinct situations, and it is essential to discover a model for estimating their oil formation volume factors which are necessary for studying and simulating the reservoirs. There are different correlations for estimating this, but most of them have large errors (at least in some points) and cannot be tuned for a specific oil. In this paper, using a wide range of experimental data points, an artificial neural network model (ANN) has been created. In which its internal parameters (number of hidden layers, number of neurons of each layer and forward or backward propagation) are optimized by a genetic algorithm to improve the accuracy of the model. In addition, four genetic programming (GP)-based models have been represented to predict the oil formation volume factor In these models, the accuracy and the simplicity of each equation are surveyed. As well as, the effect of modifying of the internal parameters of the genetic programming (by using some other values for its nodes or changing the tree depth) on the created model. Finally, the ANN and GP models are compared with fifteen other models of the most common previously introduced ones. Results show that the optimized artificial neural network is the most accurate and genetic programming is the most flexible model, which lets the user set its accuracy and simplicity. Results also recommend not adding another operator to the basic operators of the genetic programming.

It is difficult to forecast the well productivity because of the complexity of vertical and horizontal developments in fluvial facies reservoir. This paper proposes a method based on Principal Component Analysis and Artificial Neural Network to predict well productivity of fluvial facies reservoir. The method summarizes the statistical reservoir factors and engineering factors that affect the well productivity, extracts information by applying the principal component analysis method and approximates arbitrary functions of the neural network to realize an accurate and efficient prediction on the fluvial facies reservoir well productivity. This method provides an effective way for forecasting the productivity of fluvial facies reservoir which is affected by multi-factors and complex mechanism. The study result shows that this method is a practical, effective, accurate and indirect productivity forecast method and is suitable for field application.

As a serious problem in drilling operation, wellbore instability restricts efficient development of shale gas. The interaction between the drilling fluid and shale with hydration swelling property would have impact on the generation and propagation mechanism of cracks in shale formation, leading to wellbore instability. In order to investigate the influence of the hydration swelling on the crack propagation, mineral components and physicochemical properties of shale from the Lower Silurian Longmaxi Formation (LF) were investigated by using the XRD analysis, cation exchange capabilities (CEC) analysis, and SEM observation, and we researched the hydration mechanism of LF shale. Results show that quartz and clay mineral are dominated in mineral composition, and illite content averaged 67% in clay mineral. Meanwhile, CEC of the LF shale are 94.4 mmol/kg. The process of water intruding inside shale along microcracks was able to be observed through high power microscope, meanwhile, the hydration swelling stress would concentrate at the crack tip. The microcracks would propagate, bifurcate and connect with each other, with increase of water immersing time, and it would ultimately develop into macro-fracture. Moreover, the macrocracks extend and coalesce along the bedding, resulting in the rock failure into blocks. Hydration swelling is one of the major causes that lead to wellbore instability of the LF shale, and therefore improving sealing capacity and inhibition of drilling fluid system is an effective measure to stabilize a borehole.

Because of high cost and pollution of oil-based drilling fluid, the water-based drilling fluid is increasingly used now. However, bedding planes and micro-cracks are rich in shale formation. When water-based drilling fluid contacts formation rock, it causes the propagation of crack and invasion of drilling fluid, which decrease shale strength and cause wellbore instability. In this paper, we analyzed influence of water-based drilling fluid on shale strength and failure mode by mechanics experiment. Based on those experimental results, considering the effect of bedding plane and drilling time, we established modeling of wellbore stability for shale formation. The result from this model indicates that in certain azimuth of horizontal well, collapsing pressure increases dramatically due to shale failure along with bedding plane. In drilling operation, those azimuths are supposed to be avoided. This model is applicable for predication of collapsing pressure in shale formation and offers reference for choosing suitable mud weight.

In the current research, a new approach constructed based on artificial intelligence concept is introduced to determine water/oil relative permeability at various conditions. To attain an effective tool, various artificial intelligence approaches such as artificial neural network (ANN), hybrid of genetic algorithm and particle swarm optimization (HGAPSO) are examined. Intrinsic potential of feed-forward artificial neural network (ANN) optimized by different optimization algorithms are composed to estimate water/oil relative permeability. The optimization methods such as genetic algorithm, particle swarm optimization and hybrid approach of them are implemented to obtain optimal connection weights involved in the developed smart technique. The constructed intelligent models are evaluated by utilizing extensive experimental data reported in open literature. Results obtained from the proposed intelligent tools were compared with the corresponding experimental relative permeability data. The average absolute deviation between the model predictions and the relevant experimental data was found to be less than 0.1% for hybrid genetic algorithm and particle swarm optimization technique. It is expected that implication of HGAPSO-ANN in relative permeability of water/oil estimation leads to more reliable water/oil relative permeability predictions, resulting in design of more comprehensive simulation and further plans for reservoir production and management.

The application of a recent optimization technique, the artificial bee colony (ABC), was investigated in the context of finding the optimal well locations. The ABC performance was compared with the corresponding results from the particle swarm optimization (PSO) algorithm, under essentially similar conditions. Treatment of out-of-boundary solution vectors was accomplished via the Periodic boundary condition (PBC), which presumably accelerates convergence towards the global optimum. Stochastic searches were initiated from several random staring points, to minimize starting-point dependency in the established results. The optimizations were aimed at maximizing the Net Present Value (NPV) objective function over the considered oilfield production durations. To deal with the issue of reservoir heterogeneity, random permeability was applied via normal/uniform distribution functions. In addition, the issue of increased number of optimization parameters was address, by considering scenarios with multiple injector and producer wells, and cases with deviated wells in a real reservoir model. The typical results prove ABC to excel PSO (in the cases studied) after relatively short optimization cycles, indicating the great premise of ABC methodology to be used for well-optimization purposes.

Water shutoff in ultralow temperature reservoirs has received great attention in recent years. In previous study, we reported a phenol-formaldehyde-based gel formula with ammonium salt which can provide a gelation time between 2 hrs and 2 days at 25 °C. However, systematic evaluation and field recommendations of this gel formula when encountering complex reservoirs environment are not addressed. In this paper, how and why such practical considerations as water composition, temperature, pH, weight ratio of formaldehyde to resorcinol and contaminant Fe³⁺ to affect the gelation performance are examined. Brookfield DV-III and scanning electron microscopy (SEM) are employed respectively for viscosity measurement and microstructure analysis. SEM results further illustrate the mechanism of the effect of salinity on gelation performance. It reveals that crosslinking done by covalent bond has great advantage for gel stability under high salinity environment. The target gel formula can provide desirable gelation time below 60 °C, perfect for 15-45 °C, while it is unfeasible to use high salinity to delay gelation at 60 °C. We summarized the effect of salinity on gelation performance of different gel formulas from the present study and published literature. The summarized data can provide important guideline for gel formula design before conducting any kinds of experiments. The variation of gelation performance at different salinity may be dominated by the interaction between crosslinker-salt-polymer, not only limited to “charge-screening effect” and “ion association” proposed by several Authors. We hope the analysis encouraging further investigations. Some recommendations for field application of this gel are given in the end of this paper.

The remained oil in the reservoir after conventional water-flooding processes, forms a dispersed phase in the form of oil drops which is trapped by capillary forces and is almost about 70% of the original oil in the place (OOIP). To reduce oil residual saturation in laboratory experiments and field projects, surfactant flooding is effective via decreasing the interfacial tension mobility ratio between oil and water phases. Estimation of the role of design variables, like chemical concentrations, partition coefficient and injection rate in different performance quantities, considering a heterogeneous and multiphase oil reservoir is a critical stage for optimal design. Increasing demand for oil production from water-flooded reservoirs has caused an increasing interest in surfactant-polymer (SP) and alkali-surfactant-polymer (ASP). Modeling minimizes the risk of high cost of chemicals by improving our insight of process. In the present paper, a surfactant compositional flood model for a three-component (water, petroleum and surfactant), two phase (aqueous and oleic) system is studied. A homogeneous, two-dimensional, isothermal reservoir with no free gas or alkali is assumed. The governing equations are in three categories: the continuity equations for the transport of each component, Darcy's equation for the transport of each phase and other auxiliary equations. The equations are solved by finite-differences using a procedure implicit in pressure and explicit in saturation. The validation of the model is achieved through comparing the modeling results with CMG simulators and Buckley-Leverett theory. The results of modeling showed good agreement with CMG results, and the comparison with Buckley-Leverett theory is explained according to different assumptions. After validation of the model, in order to investigate sensitivity analysis, the effects of system variables (partition coefficient, surface tension, oil viscosity and surface injection concentration) and performance variable (cumulative oil recovery) are studied. Finally, the comparison of oil recovery between water-flooding and surfactant-flooding was done. The results showed higher oil recovery with changes in capillary number when the partition coefficient is greater than unity. Increasing oil viscosity resulted in decreasing the oil recovery by changing in fractional flow. Moreover, it was concluded that the oil recovery was enhanced by increasing surfactant injection concentration. The oil recovery was increased when surfactant was injected to the system and this result was obtained by comparing water-flooding and surfactant-flooding.

Distribution laws of casing external pressure, which are obtained by different scholars in different conditions, are not the same. Thus, a model to calculate the external pressure of casing is established with finite element method. In the model a contact is built between the outer wall of the casing and the inner wall of the cement sheath. The casing external pressure can be got through extracting contact force of results. The numerical results and analysis show that: The largest casing external pressure exists in the direction of minimum horizontal stress of formation rather than in the direction of the maximum horizontal stress. There exists such matching between the cement sheath elastic modulus and formation elastic modulus: When the elastic modulus of the cement sheath is small, reducing its value is conducive to reduce the casing external pressure and to prolong casing service life. When the elastic modulus of the cement sheath is large, increasing its value is conducive to reduce the casing external pressure and to prolong casing service life. The casing external pressure will become large with the increase of Poisson's ratio of cement sheath. With the increase of the degree of the formation stress unevenness, the maximum casing external pressure increases and the smallest external decreases. The increasing of the non-uniformity degree of formation stress makes the non-uniformity degree of casing external pressure and the risk of casing failure increase. The study can provide certain reference for drilling workers to take measures to prolong service life of casing.