Lessons learned from hydrothermal to hot dry rock exploration and production

In this paper,we investigate geothermal exploration and production in 189 hydrothermal projects and 42 hot dry rock projects around the world.The hydrothermal fields for a working hydrothermal system to generate electricity should have the elements of heat source,water-saturated porous or fractured reservoir,caprock,heat transfer pathway,and good heat preservation condition and geothermal power energy intensity of 10-20 MW per km^(2)within at least 5 km^(2)area in tectonically active region.The hot water or steam flow rate in this hydrothermal system is normally larger than 40 L/s with temperature of 150℃or above.The power generated from enhanced geothermal system(EGS)in hot dry rock projects are generally less than 2 MW because the flow rate in most cases is much less than 40 L/s even with the hydraulic fractures using the modern stimulation technology learned from the oil and gas industry.The natural fracture in the subsurface is generally beneficial to the hydraulic fracturing and heat recovery in the hot dry rock.Moreover,the hydraulic fracture parameters,injection rate and well spacing,drilling strategy should be properly designed to avoid the short-circuit between injector and producer and low heat productivity.In the future,CO^(2)enhanced geothermal recovery associated with CO^(2)sequestration in the high temperature oil,gas,and geothermal fields maybe a good choice.On the other hand,both nearreal-time seismic monitoring to limit the pumping rate and the closed-loop of the Eavor-Loop style system without hydraulic fracture can contribute greatly to heat recovery of hot dry rocks and mitigate the risks of the hydraulic fracturing induced earthquake.Furthermore,the hybrid solar and geothermal system performs better than the stand-alone geothermal system.

Sensitivity analysis of borehole thermal energy storage: examining key factors for system optimization

Borehole thermal energy storage(BTES)systems have garnered significant attention owing to their efficacy in storing thermal energy for heating and cooling applications.Accurate modeling is paramount for ensuring the precise design and operation of BTES systems.This study conducts a sensitivity analysis of BTES modeling by employing a comparative investigation of five distinct parameters on a wedge-shaped model,with implications extendable to a cylindrical configuration.The parameters examined included two design factors(well spacing and grout thermal conductivity),two operational variables(charging and discharging rates),and one geological attribute(soil thermal conductivity).Finite element simulations were carried out for the sensitivity analysis to evaluate the round-trip efficiency,both on a per-cycle basis and cumulatively over three years of operation,serving as performance metrics.The results showed varying degrees of sensitivity across different models to changes in these parameters.In particular,the round-trip efficiency exhibited a greater sensitivity to changes in spacing and volumetric flow rate.Furthermore,this study underscores the importance of considering the impact of the soil and grout-material thermal conductivities on the BTES-system performance over time.An optimized scenario is modelled and compared with the base case,over a comparative assessment based on a 10-year simulation.The analysis revealed that,at the end of the 10-year period,the optimized BTES model achieved a cycle efficiency of 83.4%.This sensitivity analysis provides valuable insights into the merits and constraints of diverse BTES modeling methodologies,aiding in the selection of appropriate modeling tools for BTES system design and operation.

深层干热岩水力剪切压裂认识与实践

深层干热岩水力压裂形成的裂缝网络是地下"冷注、热采"循环系统的流体流动和换热通道。注采循环井的"注不进、采不出"实质是水力压裂未成功建立沟通注水井和采热井之间的导流裂缝网络系统,该过程由流固换热(T)-流体流动(H)-裂缝形变(M)-化学溶蚀(C)耦合作用决定。通过THMC耦合开展室内测试和数值模拟研究发现:干热岩体内天然裂缝的法向剪胀形变开度是压裂改造的前提和机理,水平滑移量达到5 mm时,粗糙度对裂缝开度的影响逐渐消失,即裂缝的总开度几乎全为有效导流开度;低排量、低温的长期注入并不能快速消耗储热岩体的热能,天然裂缝的热诱导开度影响范围在5 m以内,提高排量是进一步扩大天然裂缝导流能力改善范围的必要条件;近井地带热交换(TH)形成的热诱导开度对导流开度的贡献率最高达92%,大于9.4 m的远井区域主要依靠水力剪胀作用(M)提高导流能力,其对导流开度贡献率从50%逐渐上升至99%;注入冷流体的不断升温,加剧硅质矿物的溶解能力,其最大化学溶蚀诱导开度为0.48 mm,对总导流开度贡献率最大为16.3%。

Key factors controlling shale oil enrichment in saline lacustrine rift basin:implications from two shale oil wells in Dongpu Depression,Bohai Bay Basin

Comparative analyses of petroleum generation potential,reservoir volume,frackability,and oil mobility were conducted on 102 shale cores from the Dongpu Depression.Results show the shale has high organic matter contents composed of oil-prone type I and type II kerogens within the oil window.Various types of pores and fractures exist in the shale,with a porosity of up to 14.9%.The shale has high brittle mineral contents,extensive fractures,and high potential for oil mobility due to high seepage capacity and overpressure.Although the petroleum generation potential of the shale at Well PS18-8 is relatively greater than that at Well PS18-1,oil content of the latter is greater due to the greater TOC.The porosity and fracture density observed in Well PS18-1 are greater and more conducive to shale oil enrichment.Although the shales in Wells PS18-1 and PS18-8 have similar brittle mineral contents,the former is more favorable for anthropogenic fracturing due to a higher preexisting fracture density.Besides,the shale at Well PS18-1 has a higher seepage capacity and overpressure and therefore a higher oil mobility.The fracture density and overpressure play key roles in shale oil enrichment.

Hydrocarbon generation history constrained by thermal history and hydrocarbon generation kinetics:A case study of the Dongpu Depression,Bohai Bay Basin,China

With the increasing exploration and development of typical hydrocarbon-rich depressions,such as the Dongpu Depression,the exploitation difficulty of shallow formations is increasing.There is an urgent need to clarify the hydrocarbon generation mode and hydrocarbon generation histories in deep formations.In this study,a gold tube-autoclave closed system was used to simulate the hydrocarbon generation processes and establish the hydrocarbon generation mode of different types of kerogen.Then,constrained by the thermal history and hydrocarbon generation kinetics,hydrocarbon generation histories were modeled.The results show that hydrocarbon generation evolution can be divided into five stages,and the maturity of each stage is different.The hydrocarbon generation history of the source rocks of the Shahejie 3 Formation mainly dates from the early depositional period of the Shahejie 1 Formation to the middle depositional period of the Dongying Formation.Hydrocarbon generation history constrained by thermal history and hydrocarbon generation kinetics is more in line with actual geological conditions.Moreover,this research can provide important hydrocarbon generation parameters for deep oil and gas exploration and exploitation of the Shahejie 3 Formation in the Dongpu Depression.

Application of artificial intelligence to forecast hydrocarbon production from shales

Artificial intelligence(AI)methods and applications have recently gained a great deal of attention in many areas,including fields of mathematics,neuroscience,economics,engineering,linguistics,gaming,and many others.This is due to the surge of innovative and sophisticated AI techniques applications to highly complex problems as well as the powerful new developments in high speed computing.Various applications of AI in everyday life include machine learning,pattern recognition,robotics,data processing and analysis,etc.The oil and gas industry is not behind either,in fact,AI techniques have recently been applied to estimate PVT properties,optimize production,predict recoverable hydrocarbons,optimize well placement using pattern recognition,optimize hydraulic fracture design,and to aid in reservoir characterization efforts.In this study,three different AI models are trained and used to forecast hydrocarbon production from hydraulically fractured wells.Two vastly used artificial intelligence methods,namely the Least Square Support Vector Machine(LSSVM)and the Artificial Neural Networks(ANN),are compared to a traditional curve fitting method known as Response Surface Model(RSM)using second order polynomial equations to determine production from shales.The objective of this work is to further explore the potential of AI in the oil and gas industry.Eight parameters are considered as input factors to build the model:reservoir permeability,initial dissolved gas-oil ratio,rock compressibility,gas relative permeability,slope of gas oil ratio,initial reservoir pressure,flowing bottom hole pressure,and hydraulic fracture spacing.The range of values used for these parameters resemble real field scenarios from prolific shale plays such as the Eagle Ford,Bakken,and the Niobrara in the United States.Production data consists of oil recovery factor and produced gas-oil ratio(GOR)generated from a generic hydraulically fractured reservoir model using a commercial simulator.The Box-Behnken experiment design was used to minimize the number of simulations for this study.Five time-based models(for production periods of 90 days,1 year,5 years,10 years,and 15 years)and one rate-based model(when oil rate drops to 5 bbl/day/fracture)were considered.Particle Swarm Optimization(PSO)routine is used in all three surrogate models to obtain the associated model parameters.Models were trained using 80%of all data generated through simulation while 20%was used for testing of the models.All models were evaluated by measuring the goodness of fit through the coefficient of determination(R2)and the Normalized Root Mean Square Error(NRMSE).Results show that RSM and LSSVM have very accurate oil recovery forecasting capabilities while LSSVM shows the best performance for complex GOR behavior.Furthermore,all surrogate models are shown to serve as reliable proxy reservoir models useful for fast fluid recovery forecasts and sensitivity analyses.

Impact of pyrite on shale gas enrichment——a case study of the Lower Silurian Longmaxi Formation in southeast Sichuan Basin

Pyrite is one of the important components of shale and plays a crucial role in shale gas enrichment.However,currently there are just a few studies on this subject matter.Therefore,the characteristics of pyrite in organic-rich shale section of the Longmaxi Formation and its impact on shale gas enrichment was studied in this paper by using outcrops,drilling cores,thin sections and test data.Result shows that pyrite occurred in different forms(macro-micro scale)in the Longmaxi Formation in the southeast Sichuan Basin.The formation and content of pyrite has a close relation with TOC content.Pyrite may catalyze the hydrocarbon generation of organic matter.Interparticle pores within the pyrite framboids and organic matter pores in the pyrite-organic matter complex are welldeveloped in the Longmaxi Shale,which serves as a major reservoir space for shale gas.Pyrite can promote shale gas enrichment by absorbing shale gas on its surface and preserving free gas in the interparticle pores and organic matter pores.In addition,as a kind of brittle mineral,pyrite can improve the brittleness of shale reservoir and increase the micro-nano pore system in shale reservoir,thereby improving the transmission performance of shale reservoir and boosting shale gas recovery.

Simplification workflow for hydraulically fractured reservoirs

Production from unconventional formations,such as shales,has significantly increased in recent years by stimulating large portions of a reservoir through the application of horizontal drilling and hydraulic fracturing.Although oil shales are heavily dependent on oil prices,production forecasts remain positive in the North-American region.Due to the complexity of hydraulically fractured tight formations,reservoir numerical simulation has become the standard tool to assess and predict production performance from these unconventional resources.Many of these unconventional fields are immense,consisting of multistage and multiwell projects,which results in impractical simulation run times.Hence,simplification of large-scale simulation models is now common both in the industry and academia.Typical simplified models such as the“single fracture”approach do not often capture the physics of large-scale projects which results in inaccurate results.In this paper we present a simple,yet rigorous workflow that generates simplified representative models in order to achieve low simulation run times while capturing physical phenomena which is fundamental for accurate calculations.The proposed workflow is based on consideration of representative portions of a large-scale model followed by postprocess scaling to obtain desired full model results.The simplified models that result from the application of the proposed workflow for a single well and a multiwell case are compared to full-scale models and the“single fracture”model.Comparison of fluid rates and cumulative production show that accurate results are possible for simplified models if all important components for a particular case are taken into account.Finally,application of the workflow is shown for a heterogeneous field case where prediction studies can be carried out.