Sun, Zheng (China University of Petroleum at Beijing, Texas A&M University) | Shi, Juntai (China University of Petroleum at Beijing) | Yang, Zhaopeng (RIPED, CNPC) | Wang, Cai (RIPED, CNPC) | Gou, Tuobin (Lukeqin Oil Production Plant of Tuha Oilfield Company, PetroChina) | He, Minxia (China University of Petroleum at Beijing) | Zhao, Wen (China University of Petroleum at Beijing) | Yao, Tianfu (China University of Petroleum at Beijing) | Wu, Jiayi (China University of Petroleum at Beijing) | Li, Xiangfang (China University of Petroleum at Beijing)
Much attention has been attracted by the successful development of shale gas reservoir in recent decades. Correspondingly, research aspects of shale gas reservoirs become more and more heat among the academic community, especially in the fields of nanoscale gas transport mechanisms as well as the storage modes. Fascinated by the craft interactions exerted by organic or inorganic shale surface, drastic discrepancy takes place in terms of the gas behavior inside the nanoscale dimension and that in conventional dimension. It is crucial to figure out the exact influence on shale gas recovery and overall production efficiency due to the above large difference. Notably, this paper is designed to comprehensively explore the methane storage behavior in shale nanopores, expecting to provide the direct relationship between adsorption gas and free gas content under various environmental conditions. Also, a novel and simple prediction method with regard to ultimate gas recovery is proposed, which is connected to the pore size distribution and formation pressure. First of all, the gas storage modes in a single nanopore with defined pore size are analyzed seriously. As a result, the evaluation model is constructed for adsorption gas and free gas content in a single nanopore. After that, an upscaling method is applied to extend the adaptiability of the model from single nanopore to nanoporous modia. Finally, sensitivity factor analysis work is performed and a recovery prediction methodology is developed. Results suggest that the adsorption gas content will be a larger contribution to total gas content when it comes to small pore radius and low formation pressure. In contrast, free gas content will increase with the increasing pressure and pore size. More importantly, pore size distribution characteristic has a key impact on gas storage modes and ultimate gas recovery. The high proportion of small nanopores plays a detrimental role on gas recovery, resulting in large content of adsorption gas at low pressure, which will not be produced and remain in shale gas reservoirs.
This seminar will teach participants how to identify, evaluate, and quantify risk and uncertainty in everyday oil and gas economic situations. It reviews the development of pragmatic tools, methods, and understandings for professionals that are applicable to companies of all sizes. The seminar also briefly reviews statistics, the relationship between risk and return, and hedging and future markets. Strategic thinking and planning are key elements in an organisation’s journey to maximise value to shareholders, customers, and employees. Through this workshop, attendees will go through the different processes involved in strategic planning including the elements of organisational SWOT, business scenario and options development, elaboration of strategic options and communication to stakeholders.
Decisions in E&P ventures are affected by Bias, Blindness, and Illusions (BBI) which permeate our analyses, interpretations and decisions. This one-day course examines the influence of these cognitive pitfalls and presents techniques that can be used to mitigate their impact. Bias refers to errors in thinking whereby interpretations and judgments are drawn in an illogical fashion. Blindness is the condition where we fail to see an unexpected event in plain sight. Illusions refer to misleading beliefs based on a false impression of reality.
Identification and quantification of parasequences remains a key aspect in unconventional reservoir development  demonstrated the importance of gamma ray parasequences (GRP) in unconventional play development. Currently, most of the drilling plans in unconventional plays are executed using a ‘factory made” drilling and completion program. Due to thousands of wells in an unconventional play, it is a very difficult task for operators to incorporate the fine scale reservoir characterization in time for drilling plan.
Currently the upward dirtying and upward cleaning parasequences in shale plays are interpreted qualitatively and manually by a human interpreter on individual well logs. We believe these parasequences hold key information about the underlying geology and their quantification can provide key insights into the depositional environment and hence reservoir quality. Incorporating this information in due time for drilling and completion can aid the decision making process on well placement and hydraulic fracturing design.
In this work, we handle the reservoir characterization challenge on two fronts: we first provide a statistical filtering approach to interpret the parasequences in a well log and then use machine assisted application on other wells in the area of interest. We then use Least-squares fit to obtain slopes of these parasequences. Furthermore, we map these slopes and compare them to the conventional parasequence thickness map to provide quantitative well log attributes to help aid the geologic interpretation.
Unconventional play development has key differences to that of a conventional play development. In a conventional porosity, permeability etc. are the key drivers for production. Well spacing and landing the best zone and hydraulic fracturing guide the production performance in horizontal wells. As the well is completed with hydraulic fracturing operation, the geomechanical properties of the layer become of utmost importance (-6]).  proposed that the layered properties of the shale reservoir are highly complex and is composed of alternating brittle and ductile geological sequences also known as brittle-ductile couplets . The optimal landing zone depends on a tradeoff between the brittleness and rock properties such as total organic carbon(TOC). The good rock from the reservoir perspective which is high in TOC is generally more ductile and not a suitable candidate for hydraulic fracturing operation and vice versa.
Si, Xueqiang (Petrochina Hangzhou Research Institute of Geology) | Xu, Yang (Petrochina Hangzhou Research Institute of Geology) | Wang, Xin (Petrochina Hangzhou Research Institute of Geology) | Guo, Huajun (Petrochina Hangzhou Research Institute of Geology) | Li, Yazhe (Petrochina Hangzhou Research Institute of Geology) | Shan, Xiang (Petrochina Hangzhou Research Institute of Geology)
Sandstone can be divided into many types with reference to permeability and porosity. Some scholars and researchers have established criteria to classify tight sandstone by using porosity and permeability. Sandstone with permeability less than 1mD and porosity less than 10% could be called tight sandstone. Exploration and development of tight sandstone gas has become a hot spot of oil and gas exploration (Dai J. et al., 2002) in China. Quite recently, tight sandstone gas reservoirs of different scales have been discovered in the middle-lower Jurassic of Taibei Sag in Turpan-Hami Basin. The purposes of this paperare to analyze the texture and composition of the middle-lower Jurassic tight sandstones, investigate diagenesis type and reveal the influence of diagenesis on reservoir quality.
A pre-exploration well was drilled in the Xihu Sag of East China Sea basin, and commercial oil and gas flow had been achieved. But the oil and gas bearing trap had a big depth with low closure height and small area. The resolution of seismic data acquired by towed streamer is low, so it's difficult to obtain seismic velocity precisely. There were great risk and uncertainty in description of the trap and distribution of gas-bearing sandstone, reservoir prediction of sweet spot, direct hydrocarbon indication, and reserves assessment.
In consideration of the drilling platform on the trap, seismic acquisition technique of walkaway VSP and walk around VSP were introduced, meanwhile some innovative methods in source, receivers and geometry were applied. Twenty three-component hydrophones were composed as signal receivers which had a sample interval of ten meters in the well, two straight shot lines and two loop shot lines were designed around the drilling platform. Besides, volume and depth of air gun array were optimized, and the sailing route of seismic source vessel was planned properly in order to improve the efficiency of collecting work.
The collecting work of walkaway VSP and walk around VSP was accomplished efficiently, and more than seventy kilometers VSP seismic data was achieved. Afterwards, the new data was processed finely in company with zero offset VSP data, so high resolution VSP profiles and accurate seismic velocity were obtained. Reprocess to original seismic data acquired by towed streamer was implemented on the basis of walkaway VSP and walk around VSP data. The quality of normal seismic data was improved through reprocess constrained by walkaway VSP data, and S/N and resolution were much higher than old data. So it would be credible to research the distribution of gas-bearing sandstone and direct hydrocarbon indication using the reprocessed seismic data.
It was the first time to use joint acquisition technique of walkaway VSP and walk around VSP in offshore China which was an important breakthrough. High resolution VSP seismic profiles and precise seismic velocity could be acquired, and the data was important basis for refined evaluation of pre-exploration targets. It's very necessary to popularize and utilize these new techniques further.
Non-Darcy flow and the stress-sensitivity effect are two fundamental issues that have been widely investigated in transient pressure analysis for fractured wells. The main object of this work is to establish a semianalytical solution to quantify the combined effects of non-Darcy flow and stress sensitivity on the transient pressure behavior for a fractured horizontal well in a naturally fractured reservoir. More specifically, the Barree-Conway model is used to quantify the non-Darcy flow behavior in the hydraulic fractures (HFs), while the permeability modulus is incorporated into mathematical models to take into account the stress-sensitivity effect. In this way, the resulting nonlinearity of the mathematical models is weakened by using Pedrosa’s transform formulation. Then a semianalytical method is applied to solve the coupled nonlinear mathematical models by discretizing each HF into small segments. Furthermore, the pressure response and its corresponding derivative type curve are generated to examine the combined effects of non-Darcy flow and stress sensitivity. In particular, stress sensitivity in HF and natural-fracture (NF) subsystems can be respectively analyzed, while the assumption of an equal stress-sensitivity coefficient in the two subsystems is no longer required. It is found that non-Darcy flow mainly affects the early stage bilinear and linear flow regime, leading to an increase in pressure drop and pressure derivative. The stress-sensitivity effect is found to play a significant role in those flow regimes beyond the compound-linear flow regime. The existence of non-Darcy flow makes the effect of stress sensitivity more remarkable, especially for the low-conductivity cases, while the stress sensitivity in fractures has a negligible influence on the early time period, which is dominated by non-Darcy flow behavior. Other parameters such as storage ratio and crossflow coefficient are also analyzed and discussed. It is found from field applications that the coupled model tends to obtain the most-reasonable matching results, and for that model there is an excellent agreement between the measured and simulated pressure response.
Zhaoqi Fan* and Daoyong Yang, University of Regina, and Xiaoli Li, University of Kansas Summary Cold heavy-oil production with sand (CHOPS) has been one of the major recovery processes for developing unconsolidated heavy-oil reservoirs by taking advantage of sand production and foamy-oil flow. However, effective characterization and accurate prediction of sand production is still a challenge. In this work, a pressure-gradient-based sand-failure criterion is proposed for quantifying sand production and characterizing wormhole propagation. The criterion was then extended to a grid scale within a wormhole because the pressure gradient is constant at either a pore scale or a grid scale. This was a confirmation that the proposed sandfailure criterion can be used to characterize the sand production in a CHOPS process. Introduction In a heavy-oil reservoir, the sand flux along with the oil flowing into wells has been proved to surprisingly stimulate oil production (Smith 1988). With the advance of progressing-cavity pumps that enable the mixture of oil and sand to flow effectively, CHOPS has been extensively applied to the primary development of unconsolidated heavy-oil reservoirs in western Canada (Huang et al. 1998; Tremblay et al. 1999; Han et al. 2007; Sharifi Haddad and Gates 2015). The CHOPS wells can be found in Lloydminster Field, Provost Field in the Cold Lake Oil Sands Area, Lindbergh Field, Elk Point Field, Frog Lake Field, and in China and Kuwait (Huang et al. 1998; Dusseault 2002; Meza Diaz et al. 2003; Du et al. 2009; Sanyal and Al-Sammak 2011). The CHOPS process can be considered as an effective pretreatment for heavy-oil reservoirs before traditional thermal enhanced-oil-recovery (EOR) techniques and solvent-based injection methods because of the propagation of the wormhole network (Shokri and Babadagli 2012). Most of the sand is commonly produced during the first several months of a CHOPS well life, and the oil-production peak is usually later than the sand-production peak because of the coupling influences of sand production together with pressure depletion (Huang et al. 1998). Physically, high-permeability channels (i.e., wormholes) and foamy-oil flow are considered to be the main mechanisms dominating the CHOPS processes (Huang et al. 1998; Wang and Chen 2004; Tremblay 2005).
A random forests Rate Of Penetration (ROP) model, along with heat maps, was used to challenge and optimize the drilling parameters for new wells based on the surface drilling data acquired from previous wells. The goal was to analyze the data to observe surface drilling parameter trends aiding in increased bit life and reduced bit wear resulting in maximizing ROP and minimizing Mechanical Specific Energy (MSE).
The four key variables investigated were weight on bit (WOB), surface RPM, mud flowrate and the drilling formation. Surface drilling data for this study was utilized from wells, within a 20 mile radius, where the same bit and motor drilled the entire vertical interval to TD. Heat maps and ROP models (created using support vector regression, random forests and boosted trees) were employed for this purpose. Data was cleaned up using cutoffs (from the minimum and maximum values expected by the drilling engineer) and plotting data distributions. K-fold Cross validation was applied when generating the ROP models. The aim was to focus on the optimization of drilling parameters using surface data only, due to the lack of sub-surface data availability. Using the methodology developed, the drilling parameters could be optimized to extend bit life and reduce bit trips by maximizing ROP and minimizing MSE.
The random forests ROP model was found to be the best with a 12% mean absolute error. The error could have been reduced further by introducing additional variables into the model that capture the changes in formation mechanical properties, downhole parameters and vibrations. This paper only focuses on learnings from surface drilling data. After a certain threshold (which differed for the different formations encountered) an increase in WOB didn' t result in a corresponding increase in ROP. Moreover, most of the ROP gains were observed to be in the shallower formations drilled. For the deeper formations, it was more beneficial to reduce MSE as the ROP was relatively lower no matter what the parameters.
This study used random forests, support vector regression and boosted tree methods to generate ROP models instead of neural networks. Even though neural networks are the most extensive, random forests are generally faster and were the most accurate of the three aforementioned methods used. The less time and computational resources required when compared to neural networks made random forests an attractive option for such a study.
The development of offshore heavy oil field need to reduce investment, energy consumption for oil and gas processing and transportation, we should improve the process, in order to simplify the process by using advanced technology, reduce processing facilities, improve equipment utilization, reduce energy consumption. This paper analyzes the current new technology of heavy oil processing in domestic and foreign oil field being used and in the test phase. The heavy oil in Bohai oilfield with viscosity reduction and experimental research, applied to Bohai heavy oil dehydration conveying process, as well as the feasibility and foreground of application in offshore heavy oil processing.
There is large and increasing proportion of heavy oil in oil and gas reserves in China and how to reduce the cost to maximize the heavy oil and super heavy oil production is the biggest problem facing China's petroleum industry. Onshore oil field has been using steam drive as the main development technology. The viscosity of degassed heavy oil at reservoir temperature is 10000 ~ 50,000 mPa. s, and super heavy oil (natural asphalt) more than 50,000 mPa.s. In recent years, China's offshore heavy oil development has been increasing. There have been new heavy oil field/ block put into production. How to reduce investment and increase economic benefits of heavy oil field is the focus of consideration. However, due to high density, high viscosity and poor fluidity it is difficult to achieve economic, safe and stable transportation.
Compared with the onshore oil field heavy oil reserve, the offshore heavy oil field well depth is relatively deeper, and there are more constrains on offshore platform space, equipment deploying, and Capex/Opex. Bohai heavy oil reserve is very large, well is deep, and characteristic viscosity range is wide. The oilfield is located in the Bohai Bay area, oil containing layers are mainly Qianshan, Guantao and Minghuazhen group, and crude oil viscosity range under reservoir conditions is 50 ~ 10,000 mPa - S.