Determining the Recoverable Geothermal Resources Using a Numerical Thermo-Hydraulic Coupled Modeling in Geothermal Reservoirs

Recoverable geothermal resources are very important for geothermal development and utilization. Generally, the recovery factor is a measure of available geothermal resources in a geothermal field. However, it has been a pre-determined ratio in practice and sustainable utilization of geothermal resources was not considered in the previous calculation of recoverable resources. In this work, we have attempted to develop a method to calculate recoverable geothermal resources based on a numerical thermo-hydraulic coupled modeling of a geothermal reservoir under exploitation, with an assumption of sustainability. Taking a geothermal reservoir as an example, we demonstrate the effectiveness of the method. The recoverable geothermal resources are 6.85 × 1018 J assuming a lifetime of 100 years in a well doublet pattern for geothermal heating. We further discuss the influence of well spacing on the recoverable resources. It is found that 600 m is the optimal well spacing with maximum extracted energy that conforms to the limit of the pressure drop and no temperature drop in the production well. Under the uniform well distribution pattern for sustainable exploitation, the recovery factor is 26.2%, which is higher than the previous value of 15% when depending only on lithology. The proposed method for calculating the recoverable geothermal resources is instructive for making decisions for sustainable exploitation.

A Novel Approach to Determine the Enriched Gas Recycling during the Enriched Gas Flooding Process

A novel approach was proposed for calculating the enriched gas recovery factor based on the theory of two-phase isothermal flash calculations. First, define a new parameter, pseudo formation volume factor of enriched gas, to represent the ratio of the surface volume of produced mixture gas to underground volume of enriched gas. Two logarithmic functions were obtained by matching the flash calculation data, to characterize the relationships between pseudo formation volume factor and the produced gas-oil ratio. These two functions belong to the proportion of liquefied petroleum gas in enriched gas; the proportion is greater than 50% and less than 50%, respectively. Given measured gas-oil ratio and produced gas volume, underground volume of produced enriched gas can be calculated. Injection volume of enriched gas is known; therefore, recovery factor of enriched gas is the ratio of produced to injected volume of enriched gas. This approach is simply to calculate enriched gas recovery factor, because of only needs three parameters, which can be measured directly. New approach was compared to numerical simulation results; mean error is 12%. In addition, new approach can effectively avoid the influence of lean gas on the calculation of enriched gas recycling. Three stages of enriched gas recovery factors in field Z were calculated, and the mean error is 5.62% compared to the field analysis, which proves that the new approach’s correctness and practicability.

The effect of gravity drainage mechanism on oil recovery by reservoir simulation; a case study in an Iranian highly fractured reservoir

A comprehensive reservoir simulation study was performed on an oil field that had a wide fracture network and could be considered a typical example of highly fractured reservoirs in Iran. This field is located in southwest of Iran in Zagros sedimentary basin among several neighborhood fields with relatively considerable fractured networks. In this reservoir, the pressure drops below the saturation pressure and causes the formation of a secondary gas cap. This can help to better assess the gravity drainage phenomenon. We decided to investigate and track the effect of gravity drainage mechanism on the recovery factor of oil production in this field. In this study, after/before the implementation of gas injection scenarios with different discharges, the contribution of gravity drainage mechanism to the recovery factor was found more than 50%. Considering that a relatively large number of studies have been conducted on this field simultaneously with the growth of information from different aspects and this study is the last and most comprehensive study and also the results are extracted from real field data using existing reservoir simulators, it is of special importance and can be used by researchers.

Study of the Effect of Wetting on Viscous Fingering Before and After Breakthrough by Lattice Boltzmann Simulations

We present a suite of numerical simulations of two-phase flow through a 2D model of a porous medium using the Rothman-Keller Lattice Boltzmann Method to study the effect of viscous fingering on the recovery factor as a function of viscosity ratio and wetting angle. This suite involves simulations spanning wetting angles from non-wetting to perfectly wetting and viscosity ratios spanning from 0.01 through 100. Each simulation is initialized with a porous model that is fully saturated with a "blue" fluid, and a "red" fluid is then injected from the left. The simulation parameters are set such that the capillary number is 10, well above the threshold for viscous fingering, and with a Reynolds number of 0.2 which is well below the transition to turbulence and small enough such that inertial effects are negligible. Each simulation involves the "red" fluid being injected from the left at a constant rate such in accord with the specified capillary number and Reynolds number until the red fluid breaks through the right side of the model. As expected, the dominant effect is the viscosity ratio, with narrow tendrils (viscous fingering) occurring for small viscosity ratios with M ≪ 1, and an almost linear front occurring for viscosity ratios above unity. The wetting angle is found to have a more subtle and complicated role. For low wetting angles (highly wetting injected fluids), the finger morphology is more rounded whereas for high wetting angles, the fingers become narrow. The effect of wettability on saturation (recovery factor) is more complex than the expected increase in recovery factor as the wetting angle is decreased, with specific wetting angles at certain viscosity ratios that optimize yield. This complex phase space landscape with hills, valleys and ridges suggests the dynamics of flow has a complex relationship with the geometry of the medium and hydrodynamical parameters, and hence recovery factors. This kind of behavior potentially has immense significance to Enhanced Oil Recovery (EOR). For the case of low viscosity ratio, the flow after breakthrough is localized mainly through narrow fingers but these evolve and broaden and the saturation continues to increase albeit at a reduced rate. For this reason, the recovery factor continues to increase after breakthrough and approaches over 90% after 10 times the breakthrough time.

Recovery Factor Improvement; A Success Story of Improving 10% of RF in Greater Natih Reservoirs, North of Oman

Recovery Factor Improvement (RFI) is a process to check the hydrocarbon production efficiency by incorporating the actual static and dynamic field data, as well as the way how the field being operated. This has been a common process within Shell's portfolio since 2018 (Ref; Muggeridge et al., 2013 & Smalley et al., 2009). The approach has been developed to stimulate the identification of new opportunities to increase the recovery from the existing fields and to aid the maturation of these opportunities into the Opportunity Realization Process. There are four (4) factors that affected overall reservoir recovery factor, they are: Pressure efficiency; related to which pressure can be reduced in the reservoir as dictated by the relevant facilities and wells.Drainage Efficiency; the proportion of the in-place hydrocarbon that is pressure-connected directly to at least one producing well on a production timescale.The "secondary pay" efficiency; takes into account the volumes of poorer quality rock in which the gas remains at pressure above the lowest pressure just outside the wellbore (Pf) when the reservoir is abandoned.Cut-off Efficiency; the proportion of hydrocarbon that is lost due to non-production of the tail.This approach was applied in the dry gas Natih Reservoir fields in the PDO concession area. Before the implementation of RFI, the average recovery factor for Natih was around 70%. This was considered low for a homogenous-dry gas reservoir. The targeted Natih fields were benchmarked against each other with a total of 11 fields with similar reservoir properties. Post the benchmarking exercise, the expected field recovery factor is approximately ~90-93%. The team managed to map out the opportunities to achieve the targeted RF and identified the road map activities. The activities are mainly related to: production optimization: retubing, re-stimulation reduce drainage: infill drilling, horizontal well reduce the field intake through compression The outcome of the mapping was then further analyzed through integrated framework to be matured as a firm-project. The new proposed activities are expected to add around 9% additional recovery to the existing fields. There will be a remaining activities which will be studied in the future, example infill wells and intelligent completions. These will close the gap to TQ and add other addition RF of 11-13%. As conclusion, the RFI was seen as a structured approach to better understanding the field recovery factor based on the integrated surface and subsurface data with a robust analysis to trigger opportunity identification linked to RFI elements. It is similar concept as sweating the asset by generating limit diagram for each recovery mechanism & the road map to achieve the maximum limit. This paper will highlight the Natih Fields RFI analysis, highlighting the key learning and challenges.

Experimental Investigation of Hydrocarbon Gas Huff-N-Puff Injection into the Live-Oil Window of Eagle Ford

The hydrocarbon gas huff and puff (HnP) technique has been used to improve oil production in unconventional oil reservoirs where excess capacity of produced gas is available and hydrocarbon prices are in a range to result in an economically viable case. Eagle Ford (EF) is one of the largest unconventional oil plays in the United State where HnP has been applied for enhanced oil recovery (EOR) at reservoirs within various oil windows. Our previously published Huff-n-puff results on dead oil with produced gas from Eagle Ford (EF) showed the recovery factor of hydrocarbon varying from 40 to 58%. The objective of this paper is to extend the experiments to live oil with EF core plugs to investigate the mechanisms of HnP which are affected by the composition of injected gas and resident oil, injection and soaking time as well as injection/depletion pressure gradient. Eagle Ford live oil and natural gas produced from the target area were used for HnP tests. Four representative core plugs were used with the tests conducted at reservoir conditions (125 °C and 3,500 psi). The live oil experiments with four reservoir core plugs showed an improvement in oil recovery with recovery factor (RF) varying from 19.5 to 33 % in six cycles of HnP, whereas the primary depletion on the same core plug showed RF below 11 %. A lower recovery factor of HnP from live oil saturated core in this study was observed as compared to dead oil saturated core reported in a previous publication. It is attributed to a lesser diffusion effect on mass transfer between injected gas and resident oil when the core is saturated with live oil. This behavior is displayed by the pressure decline curve during the first soaking period. A sharper diffusion pressure decline occurred in the dead oil saturated core plug where a higher concentration gradient between injected gas and resident oil drives a faster gas transport into the oil due to the molecular diffusion during the soaking period.

The Effect of Relative Permeability Hysteresis on the Design of an Optimal Water-Alternating-Gas (WAG) Process

Summary Water-alternating gas (WAG) as a tertiary recovery method is applied to oil reservoirs at a later stage of reservoir life to more or less success depending on field and operation. Uncertainty in WAG optimization has been shown to be dependent on several factors including reservoir characterization, WAG timing, and its operation. In this paper, we comprehensively explore WAG optimization in the context of WAG operating parameters and hysteresis, the first paper to explore both simultaneously. WAG operating parameters have been analyzed and optimized at both the core and field scale with a general conclusion that the timing, miscibility, WAG ratio, cycle time, and number of cycles play a varying role in the WAG optimization. Reservoir characterization has considered well configuration, oil type, rock properties, and hysteresis in relative permeability. Due to the cyclic nature of WAG and the dependency of the relative permeability on the saturation history, the relative permeability hysteresis modeling plays a key role in WAG performance whereby different hysteresis models will predict different results, as shown in literature. In this paper, we consider the choice of the hysteresis model and WAG operating parameters on WAG optimization. First, a sensitivity analysis is performed to evaluate the effect of hysteresis models (no hysteresis, Carlson, and Killough) on a large number of WAG development scenarios sampled by the Latin hypercube sampling method. Next, optimizations were conducted to compare and analyze the optimum recovery factor and corresponding optimal WAG operating parameters for various combinations of hysteresis models. The results of the study indicate that excluding hysteresis modeling from simulations would likely lead to a higher predicted produced volume of the nonwetting phases, that is, oil and gas, and a lower predicted produced volume of the wetting phase, that is, water. Also, the optimal recovery factor as well as the optimal WAG operating parameters can be significantly affected by the choice of the hysteresis models.

Performance Mechanism of Hydrogel for Enhanced Oil Recovery: A Numerical Simulation Study Based on the Phase-Field Approach

Hydrogels are increasingly applied in oil recovery processes. This leads to more controlled flow of fluids in porous media. In this process, hydrogel is injected to the reservoir to block the high permeability areas. The trapped oil in low permeability regions, is then swept by water flooding. pH-sensitive hydrogel microspheres were synthesized in another work of the authors, which effectively increased the oil recovery factor in experimental studies. In this communication, phase-field approach was used to simulate this process and to obtain the tuning parameters of the model including thickness of the contact surface(є), phase transform parameter(M0), excess free energy(\(\wedge\)), and interfacial tension. Diffusion of hydrogels was studied by Cahn–Hilliard conservative approach and the breakage, deformation, and plugging mechanisms were analyzed, based on pressure drop variations in micromodel. Moreover, Effective parameters on oil recovery factor were analyzed. Results indicated a good agreement between experimental and modeling studies of oil recovery factor in water and hydrogel flooding with absolute errors of 2.29% and 4.06%, respectively. The recovery factor was calculated using a statistical method which was in good agreement with the modeling results. The tuned parameters of the model were reported as, є= 111.7µm, M0= 5*10-13m3/s, \(\wedge\)=-0.0003 J/m3, and δ = 2×10-5 Pa.s.

RESERVOIR PERFORMANCE ANALYSIS USING MATERIAL BALANCE METHOD IN GAS FIELD

The RF reservoir is a dry gas reservoir located in Northeast java offshore that has been produced since 2018. The RF reservoir has produced 2 wells with cumulative production until December 2019 is 31.83 BSCF. In January 2018 the gas production rate from the two wells was 36 MMSCFD and the reservoir pressure at the beginning of production was 2449.5 psia, peak production occurred in April 2019 with a gas flow rate of 98 MMSCFD but in December 2019 the gas production rate from both wells decreased to 30 MMSCFD with reservoir pressure decreased to 1607.8 psia. Changes in gas flow rate and pressure in the RF reservoir will affect changes in reservoir performance, so it is necessary to analyze reservoir performance to determine reservoir performance in the future with the material balance method. Based on the results the initial gas in place (IGIP) is 80.08 BSCF. The drive mechanism worked on the RF reservoir until December 2019 was a depletion drive with a recovery factor up to 88% and a current recovery factor (CRF) is 40%. The remaining gas reserves in December 2019 is 39 BSCF and the reservoir will be made a production prediction until December 2032. Based on production predictions of the four scenarios, scenario 2 was chosen as the best scenario to develop the RF reservoir with a cumulative production is 66.1 BSCF and a recovery factor of 82.6%.