Semi-Supervised Learning–Based Petrophysical Facies Division and “Sweet Spot” Identification of Low-Permeability Sandstone Reservoir

The identification of the “sweet spot” of low-permeability sandstone reservoirs is a basic research topic in the exploration and development of oil and gas fields. Lithology identification, reservoir classification based on the pore structure and physical properties, and petrophysical facies classification are common methods for low-permeability reservoir classification, but their classification effect needs to be improved. The low-permeability reservoir is characterized by low rock physical properties, small porosity and permeability distribution range, and strong heterogeneity between layers. The seepage capacity and productivity of the reservoir vary considerably. Moreover, the logging response characteristics and resistivity value are similar for low-permeability reservoirs. In addition to physical properties and oil bearing, they are also affected by factors such as complex lithology, pore structure, and other factors, making it difficult for division of reservoir petrophysical facies and “sweet spot” identification. In this study, the logging values between low-porosity and -permeability reservoirs in the Paleozoic Es3 reservoir in the M field of the Bohai Sea, and between natural gamma rays and triple porosity reservoirs are similar. Resistivity is strongly influenced by physical properties, oil content, pore structure, and clay content, and the productivity difference is obvious. In order to improve the identification accuracy of “sweet spot,” a semi-supervised learning model for petrophysical facies division is proposed. The influence of lithology and physical properties on resistivity was removed by using an artificial neural network to predict resistivity R0 saturated with pure water. Based on the logging data, the automatic clustering MRGC algorithm was used to optimize the sensitive parameters and divide the logging facies to establish the unsupervised clustering model. Then using the divided results of mercury injection data, core cast thin layers, and logging faces, the characteristics of diagenetic types, pore structure, and logging response were integrated to identify rock petrophysical facies and establish a supervised identification model. A semi-supervised learning model based on the combination of “unsupervised supervised” was extended to the whole region training prediction for “sweet spot” identification, and the prediction results of the model were in good agreement with the actual results.

Study on the Influential Factors of CO2 Storage in Low Permeability Reservoir

As the demands of tight-oil Enhanced Oil Recovery (EOR) and the controlling of anthropogenic carbon emission have become global challenges, Carbon Capture Utilization and Sequestration (CCUS) has been recognized as an effective solution to resolve both needs. However, the influential factors of carbon dioxide (CO2) geological storage in low permeability reservoirs have not been fully studied. Based on core samples from the Huang-3 area of the Ordos Basin, the feasibility and influential factors of geological CO2 sequestration in the Huang-3 area are analyzed through caprock breakthrough tests and a CO2 storage factor experiment. The results indicate that capillary trapping is the key mechanism of the sealing effect by the caprock. With the increase of caprock permeability, the breakthrough pressure and pressure difference decreased rapidly. A good exponential relationship between caprock breakthrough pressure and permeability can be summarized. The minimum breakthrough pressure of CO2 in the caprock of the Huang-3 area is 22 MPa, and the breakthrough pressure gradient is greater than 100 MPa/m. Huang-3 area is suitable for the geological sequestration of CO2, and the risk of CO2 breakthrough in the caprock is small. At the same storage percentage, the recovery factor of crude oil in larger permeability core is higher, and the storage percentage decreases with the increase of recovery factor. It turned out that a low permeability reservoir is easier to store CO2, and the storage percentage of carbon dioxide in the miscible phase is greater than that in the immiscible phase. This study can provide empirical reference for caprock selection and safety evaluation of CO2 geological storage in low permeability reservoirs within Ordos Basin.

Optimization and characterization of biosurfactant produced by indigenous Brevibacillus borstelensis isolated from a low permeability reservoir for application in MEOR

Biosurfactants are expected to be a key factor for microbial enhanced oil recovery (MEOR).

Estimation of efficiency of oil extraction with supercritical CO2 in a low-permeability reservoir

The results of experimental study of oil extraction by supercritical carbon dioxide in a low-permeability reservoir are presented. As an object of study, we selected core samples from a low-permeability oil-saturated reservoir of one of the fields in Western Siberia, which is currently being developed in the regime of depletion of reservoir energy. The contact time of supercritical carbon dioxide with composite core models in three experiments was 8, 24, and 72 hours, respectively. Based on the results of laboratory experiments, the dynamics of the penetration of carbon dioxide along the depth of the composite core model was established. The value of the oil recovery factor and it’s distribution along the length of the core model in time is given. Keywords: carbon dioxide; low-permeability reservoir; mnimum miscibility pressure; slim-tube; extraction; oil recovery.

Application of Successful New Downhole Fluid Sampling Technique in Ultra Low Permeability Reservoir in Abu Dhabi Onshore

Downhole reservoir fluids sampling in tight formations has been a continuous challenge due to various reasons. The paper presents a technique of successfully collecting downhole fluid samples for first time in ultra-low permeability reservoir having a history of deep invasion. This became possible by initiating micro-scale fractures followed by pumping out for sampling. Using this technique, downhole formation fluid samples were collected, clean-up time was optimized, in addition to acquiring in-situ stress information during the process. A preliminary assessment was performed using open hole formation evaluation logs and pore pressure measurements to identify the most suitable zones for stress measurement and fluid sampling. Single packer sleeve fracture initiation tests were performed to break down the high stress dense layers. In the reservoir rock, the stress measurement involving initiation of a micro-scale fracture was followed by pumping out formation fluid from the fractured zones to collect clean formation fluid samples. The formation breakdown and fracture closure pressure were measured successfully to calibrate minimum and maximum lateral tectonic strains which were valuable inputs for designing the hydraulic fracturing treatment. In the offset wells, fluid sampling attempts from this zone of interest have proven unsuccessful after multiple attempts involving pumping out over 300 liters because of the high depth of invasion leading to a thick flushed zone around the wellbore. The process of initiating micro-scale fractures followed by pumping out provided a high permeability flow channel for efficient fluid sampling. The near wellbore fractures resulted in pumping at higher rates and reaching the higher oil saturated zones of this deeply invaded formation. Hence, formation fluid samples were successfully collected in spite of the low permeability and high invasion typically encountered in this reservoir. Unlike the unsuccessful sampling attempts in the offset wells, this technique of initiating micro-scale fractures in the reservoir rock followed by pumping out helped in collecting formation fluid samples. This technique can be used to collect reservoir fluid samples from micro-Darcy formations and unconventional reservoirs by improving the flow through the induced fractures and thereby reducing the uncertainty that may persist in failing to collect samples from such zones.

A Study of Seepage Characteristics of Unsteady Waterflooding Development for Fractured Ultra-Low-Permeability Reservoir

Unconventional fractured ultra-low-permeability reservoirs play an important role in continental sedimentary basins in China, and their formation characteristics and seepage laws are greatly different from that of traditional reservoirs. In this paper, the influence of microfractures and unsteady waterflooding on the productivity of fractured ultra-low permeability reservoirs are studied deeply. The reservoir parameters used in the study are from an actual fractured ultra-low-permeability reservoir in Ordos Basin, where microfractures are developed but macroscopic fractures are not. The microfractures have a small opening and are widely distributed in the reservoir, so the reservoir numerical simulation model adopts the equivalent continuous matrix model to simulate waterflooding. On one hand, the physical model of micro-fractured reservoir and the permeability tensor model of the equivalent continuous matrix are established. The results show that the existence of microfractures can increase the permeability of matrix by 1.4 times. On the other hand, an ideal heterogeneous numerical simulation model composed of pure matrix and equivalent continuous matrix considering microfracture is established according to actual geological parameters of the fractured ultra-low-permeability reservoir. To simulate and compare the unsteady waterflooding and continuous waterflooding development in 10-year development under the condition of constant annual injection rate, the results indicate that unsteady waterflooding development make higher productivity and lower water cut and lower formation water saturation than that of continuous waterflooding. By conducting unsteady waterflooding development simulation for sensitivity analysis, the results demonstrate that the greater the capillary force, the better the role of capillary imbibition in a certain range, meanwhile, the unsteady waterflooding has the best exploitation effect when the value of water injection cycle time is 100 days and the fluctuation amplitude of water injection rate is 1. At the above situation, the displacement and capillary imbibition and pressure disturbance achieve the desired effect of reducing water cut and increasing oil production.