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A buried hill reservoir is a special type of bedrock reservoir, in which fractures are the important reservoir space and main percolation path. However, due to the characteristics of the buried hill reservoir such as deep burial depth and high formation pressure, the fracture width of deep formation is generally in micron level, and the randomness of spatial development brings great difficulties to logging identification and reservoir parameter calculation. Based on the fracture porosity and saturation model of the dual pore model, this paper puts forward the theory of identifying fracture type of buried hill fractured reservoir by using conductivity efficiency. The results show that (1) the fracture angle has no effect on the conductivity efficiency. And we cannot distinguish a high-angle fracture from a low-angle fracture by conductivity efficiency. (2) The values of porosity and water saturation are not directly related to the conductivity efficiency. But porosity and water saturation will affect the connectivity of water in the reservoir and indirectly affect the conductivity efficiency. (3) The conductivity efficiency of the network fracture is usually less than that of the dissolution fracture.

The McMurray Formation, NE Alberta, Canada, is one of the most significant bitumen bearing deposits worldwide. This formation deposited and reworked in fluvial, tidal, or estuarine environments results in a huge number of tidal couplets (TCs) which is consisted of mm-cm scale sandy and muddy interlayers. These couplets not only increase the geologic heterogeneity of the oil sand reservoir but also make it hard to predict the performance of in situ thermal processes. In this paper, based on literatures, lab analysis, core photos, logging, and drilling data, a quantitative characterization procedure for mm-cm scale tidal couplets was proposed. This procedure, which includes identification, classification, quantitative description, and spatial distribution prediction, was presented. Five parameters, thickness, mud volume, laminae frequency, spatial scale, and effective petrophysical properties, were selected to describe the TCs quantitatively. To show the procedure practically, TCs in the oil sand reservoir of McMurray Formation, Mackay River Project, and CNPC, were selected to demonstrate this procedure. The results indicate that the TCs are in mm-cm thickness, densely clustered, and in a variety of geometries. Based on geologic origins, these couplets were divided into four types: tidal bar couplets (TBCs), sand bar couplets (SBCs), mix flat couplets (MFCs), and tidal channel couplets (TCCs). The thickness, mud volume, and frequency were calculated by mathematical morphological processed core photos. The spatial scale of TCs was estimated by high-density well correlations. The effective petrophysical properties were estimated by bedding scale modeling and property modeling via REV. Finally, the spatial distribution of TCs was predicted by object-based modeling.

Based on the elaborate dissection of profile sections parallel and vertical with the shoreline and the forming beach-bars, the unique sedimentary succession of gravel beach-bars, “ABC” sequence, has been found, and their lithofacies and origin have been explained. The A interval is composed of poorly sorted sand and gravel, formed in the wave asymmetric zone. The B interval is composed of well-sorted gravel, formed in the breaker zone. The C interval is composed of normally graded sand, formed in the surfing zone. In the actual gravel beach-bars, three intervals are often presented in a variety of combinations, such as “ABCABC,” “BCBCBC,” “ABABAB,” and others. These findings provide an important basis for the identification and distribution prediction of beach-bar reservoirs in the ancient continental lake basins.

Stress sensitivity has always been a research hotspot in fractured-porous reservoirs and shows huge impacts on well productivity during the depletion development. Due to the continuous reservoir pressure change, accurate evaluation of stress sensitivity and its influence on well productivity is of great significance to optimize well working system. Taking horizontal well trajectory as the research object, the principal focus of this work is on the analysis of inflow performance for a horizontal well coupling stress sensitivity and reservoir pressure change in a fractured-porous reservoir. Firstly, a relationship between permeability damage rate and stress sensitivity coefficient was established to quantitatively evaluate the influence of reservoir pressure and stress sensitivity on reservoir permeability. Secondly, considering stress sensitivity and reservoir pressure drop, a set of practical productivity equations were derived for a horizontal well in a fractured-porous reservoir by adopting the equivalent seepage resistance method. Finally, the influence of relevant important factors on the inflow performance of horizontal wells was discussed in depth. Results show that a positive correlation exists between stress sensitivity coefficient and maximum permeability damage rate. At the same maximum permeability damage rate, high initial reservoir pressure corresponds to low stress sensitivity coefficient. In general, stress sensitivity coefficient mainly ranges from 0 to 0.2. Reservoir pressure change drastically affects the production dynamic characteristics of horizontal wells, and both the inflow performance curve and the production index curve decline and shrink as reservoir pressure decreases. Stress sensitivity is negatively correlated with horizontal well productivity, and the inflow performance/production index curve bends closer to bottom-hole pressure axis, and an inflection point can be observed with the aggravation of stress sensitivity. In addition, horizontal wellbore length and initial reservoir permeability also show significant effects on the inflow performance and are positively correlated with well productivity. For water cut, it has little effect on the well production when bottom-hole pressure drawdown is low, but its effect gets stronger as the drawdown becomes higher. Meaningfully, depending on these newly established productivity equations, a reasonable production system can be quantitatively optimized and achieved for the horizontal wells in fractured-porous reservoirs.

Multifractured horizontal wells are widely used in the development of tight gas reservoirs to improve the gas production and the ultimate reservoir recovery. Based on the heterogeneity characteristics of the tight gas reservoir, the homogeneous scheme and four typical heterogeneous schemes were established to simulate the production of a multifractured horizontal well. The seepage characteristics and production performance of different schemes were compared and analyzed in detail by the analysis of streamline distribution, pressure distribution, and production data. In addition, the effects of reservoir permeability level, length of horizontal well, and fracture half-length on the gas reservoir recovery were discussed. Results show that the reservoir permeability of the unfractured areas, which are located at both ends of the multifractured horizontal well, determines the seepage ability of the reservoir matrix, showing a significant impact on the long-term gas production. High reservoir permeability level, long horizontal well length, and long fracture half-length can mitigate the negative influence of heterogeneity on the gas production. Our research can provide some guidance for the layout of multifractured horizontal wells and fracturing design in heterogeneous tight gas reservoirs.

Training image (TI) is important for multipoint statistics simulation method (MPS), since it captures the spatial geological pattern of target reservoir to be modeled. Generally, one optimal TI is selected before applying MPS by evaluating the similarities between many TIs and the well interpretations of target reservoir. In this paper, we propose a new training image optimization approach based on the convolutional neural network (CNN). First, candidate TIs were randomly sampled several times to obtain the sample dataset. Then, the CNN was used to conduct transfer learning for all samples, and finally, the optimal TI of the conditioning well data is selected through the trained CNN model. By taking advantage of the strong learning ability of CNN in image feature recognition, the proposed method can automatically identify differences in spatial features between the conditioning well data and the samples of the training image. Hence, it effectively resolves the difficulty of spatial matching between discrete datapoints and grid structures. We demonstrated the applicability of our model via 2D and 3D training image selection examples. The proposed methods effectively selected the appropriate TI, and then the pretreatment techniques for improving the accuracy of continuous TI selection were achieved. Moreover, the proposed method was successfully applied to training image selection of a discrete fracture network model. Finally, sensitivity analysis was carried out to show that sufficient conditioning data volume can reduce the uncertainty of the optimization results. By comparing with the improved MDevD method, the advantages of the new method are verified in terms of efficiency and reliability.

Loss of the vast majority of heat and steam is an unavoidable problem encountered during conventional steam-assisted gravity drainage (SAGD) in extraheavy oil reservoirs. The noncondensate gas coinjection technique of reducing energy consumption and enhancing oil recovery can effectively solve this problem. Aiming at extraheavy oil with a high initial viscosity, the influence of noncondensate gases in multithermal fluids on the physical parameters of extraheavy oil was experimentally studied; the production characteristics and mechanism of multithermal fluid-assisted SAGD were studied through numerical simulation. A comparative investigation of the conventional SAGD and multithermal fluid-assisted SAGD injection schemes was conducted. The characteristics and mechanism of the steam chamber during the production processes were analyzed. The results show that a steam-gas-oil system forms in the steam chamber in the case of multithermal fluids. The steam chamber can be partitioned into four zones, and the flow of the oil mainly occurs in the steam condensation zone and the oil drainage zone. The injected multithermal fluids increase the horizontal expansion of the steam chamber, while the dissolved carbon dioxide reduces the residual oil saturation. Moreover, the nitrogen injection significantly reduces the heat loss and increases the heat utilization for multithermal fluid-assisted SAGD in developing extraheavy oil reservoirs.

The deposition and evolution of fine-grained sediments is a hot topic in fine-grained sedimentary rock studies and is important for accurately evaluating shale gas sweet spots. In this paper, the fine-grained deposition and evolution characteristics of the Wufeng-Longmaxi shales, major targets for Chinese shale gas exploration, were studied by using core observations, thin section analyses, scanning electron microscopy, geochemical analysis, and fossil identification. This work accurately identified six typical lithofacies; among them, the organic matter-rich siliceous shale facies (OMRSSF), the high-organic matter siliceous argillaceous shale facies (HOMSASF), and the medium-high organic matter low calcareous siliceous shale facies (M-HOMLCSASF) are favorable facies for shale gas exploration. The high-resolution isochronous unit in the shelf fine-grained sedimentary system was established, and the differential evolution of lithofacies in the system tract was discussed. The lithofacies deposition and differentiation in the transgressive system tract were controlled by the transgressive scale and tectonics under increasingly shallow water conditions. The lithofacies deposition and differentiation in the regressive system tract were controlled by tectonics and the preexisting lithofacies. The lithofacies in the regressive system tract had more frequent facies transitions and greater differentiation than those in the transgressive system tract, and they exhibited significant spatiotemporal inheritance. Sequential differential sedimentary sequences and symmetric differential sedimentary sequences were distinguished in the continental shelf sedimentary system. The lithofacies depocenters and subsidence centers were consistent in the transgressive system tract, while the tectonically active paleocontinent was important in the regression system tract. This study is of great significance for further high-resolution exploration of marine shale and improvement of the theory of shelf fine-grained sedimentary systems.

Determination of gas in place (GIP) is among the hotspot issues in the field of oil/gas reservoir engineering. The conventional material balance method and other relevant approaches have found widespread application in estimating GIP of a gas reservoir or well-controlled gas reserves, but they are normally not cost-effective. To calculate GIP of abnormally pressured gas reservoirs economically and accurately, this paper deduces an iteration method for GIP estimation from production data, taking into consideration the pore shrinkage of reservoir rock and the volume expansion of irreducible water, and presents a strategy for selecting an initial iteration value of GIP. The approach, termed DMBM-APGR (dynamic material balance method for abnormally pressured gas reservoirs) here, is based on two equations: dynamic material balance equation and static material balance equation for overpressured gas reservoirs. The former delineates the relationship between the quasipressure at bottomhole pressure and the one at average reservoir pressure, and the latter reflects the relationship between average reservoir pressure and cumulative gas production, both of which are rigidly demonstrated in the paper using the basic theory of gas flow through porous media and material balance principle. The method proves effective with several numerical cases under various production schedules and a field case under a variable rate/variable pressure schedule, and the calculation error of GIP does not go beyond 5% provided that the production data are credible. DMBM-APGR goes for gas reservoirs with abnormally high pressure as well as those with normal pressure in virtue of its strict theoretical foundation, which not only considers the compressibilities of rock and bound water, but also reckons with the changes in production rate and variations of gas properties as functions of pressure. The method may serve as a valuable and reliable tool in determining gas reserves.