A new method for logging identification of fluid properties in tight sandstone gas reservoirs based on gray correlation weight analysis-A case study of the Middle Jurassic Shaximiao Formation on the eastern slope of the Western Sichuan Depression, China

2021 ◽  
pp. 1-52
Author(s):  
Shaoke Feng ◽  
Runcheng Xie ◽  
Wen Zhou ◽  
Shuai Yin ◽  
Meizhou Deng ◽  
...  
Keyword(s):  
New Method ◽  
Eastern Slope ◽  
Tight Sandstone ◽  
Gas Reservoir ◽  
Western Sichuan ◽  
Fluid Property ◽  
Reservoir Fluid ◽  
Gray Correlation ◽  
Fluid Properties ◽  
Weight Analysis

Energy exploration is becoming increasingly complex worldwide, and tight sandstone gas is an important field for the future development of the oil and gas industry. For the reservoir properties of the Shaximiao Gas Reservoir on the eastern slope of the Western Sichuan Depression in the Sichuan Basin, western China, it was found that the low-resistance characteristics of the reservoir complicate the gray characteristics among reservoir fluid property parameters. Some commonly used fluid property identification techniques, such as the flow zone index method, correlation analysis method of logging parameters, and traditional mathematical statistical methods, have poor fluid property evaluation results. Therefore, how to eliminate the influence of the gray features among the reservoir parameters on the identification of reservoir fluid properties and how to accurately identify the reservoir fluid properties are urgent problems that need to be solved. In this paper, we proposed a new method for identifying the fluid properties of tight sandstone reservoirs by combining gray system theory and multivariate statistical theory. This method can perform gray correlation weight analysis on parameters (combined parameters) closely related to fluid properties; furthermore, the logging identification method based on gray correlation weight analysis is used to identify reservoir fluid properties. The results show that the gray correlation weight analysis can accurately characterize the gray characteristics of reservoir fluid parameters, and the gray comprehensive correlation weight results are in good agreement with the production status of the studied gas reservoir. We used the method to identify the fluid properties of the target layer in 58 wells in the study area, and the discrimination rate of the model was 86.5%. In addition, the new model was used to predict the reservoir fluid properties of 12 newly drilled wells in the study area, and the accuracy of the reservoir fluid property prediction was 91.67%.

Predicting Reservoir Fluid Properties from Advanced Mud Gas Data

2021 ◽  
pp. 1-9
Author(s):  
Tao Yang ◽  
Gulnar Yerkinkyzy ◽  
Knut Uleberg ◽  
Ibnu Hafidz Arief
Keyword(s):  
Machine Learning ◽  
Production Optimization ◽  
Fluid Density ◽  
Learning Models ◽  
Fluid Property ◽  
Reservoir Fluid ◽  
Study Results ◽  
Fluid Properties ◽  
Prediction Approach ◽  
Machine Learning Models

Summary In a recent paper, we published a machine learning method to quantitatively predict reservoir fluid gas/oil ratio (GOR) from advanced mud gas (AMG) data. The significant increase of the model accuracy compared to traditional modeling approaches makes it possible to estimate reservoir fluid GOR based on AMG data while drilling, before the wireline operation. This approach has clear advantages because of early access, low cost, and a continuous reservoir fluid GOR for all reservoir zones. This paper releases further study results to predict other reservoir fluid properties in addition to GOR, which is essential for geo-operations, field development plans, and production optimization. Two approaches were selected to predict other reservoir fluid properties. As illustrated by the reservoir fluid density example, we developed machine learning models for individual reservoir fluid properties for the first approach, similar to the GOR prediction approach in the previous paper. As for the second approach, instead of developing many machine learning models for individual reservoir fluid property, we investigated the essential properties for equation of state (EOS) fluid characterization: C6 and C7+ composition and the molecular weight and density of the C7+ fraction. Once these properties are in place, the entire spectrum of reservoir fluid properties can be calculated with the EOS model. The results of reservoir fluid property prediction are satisfactory with both approaches. The reservoir oil density prediction has a mean average error (MAE) of 0.039 g/cm3. The accuracy is similar to the typical density derived from the pressure gradient from wireline logging data. For the essential fluid properties required for EOS model prediction, the overall accuracy is less than the laboratory measurements but acceptable as the early phase estimations. The reservoir fluid properties predicted from the EOS model are similar to the predictions from individual machine learning models. We applied the field measured AMG data into the reservoir fluid property models and achieved good results, as illustrated by the reservoir fluid density example. The previous paper completed the methodology to predict all reservoir fluid properties based on AMG data. This work paves the way to generate a complete reservoir fluid log for all relevant reservoir fluid properties while drilling. The method has a significant business impact, providing full coverage of reservoir fluid properties along the well path in the early drilling phase. The advantage of providing reservoir fluid properties in all reservoir zones while drilling far outweighs the limitation of somewhat reduced reservoir fluid property accuracy.

scholarly journals A New Method for Fracturing Wells Reservoir Evaluation in Fractured Gas Reservoir

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Jianchun Guo ◽  
Yong Xiao ◽  
Haiyan Zhu
Keyword(s):  
Evaluation Model ◽  
New Method ◽  
Natural Fracture ◽  
Fuzzy Arithmetic ◽  
Fuzzy Evaluation ◽  
Natural Fractures ◽  
Gas Reservoir ◽  
Reservoir Evaluation ◽  
Gray Correlation ◽  
Fuzzy Logic Theory

Natural fracture is a geological phenomenon widely distributed in tight formation, and fractured gas reservoir stimulation effect mainly depends on the communication of natural fractures. Therefore it is necessary to carry out the evaluation of this reservoir and to find out the optimal natural fractures development wells. By analyzing the interactions and nonlinear relationships of the parameters, it establishes three-level index system of reservoir evaluation and proposes a new method for gas well reservoir evaluation model in fractured gas reservoir on the basis of fuzzy logic theory and multilevel gray correlation. For this method, the Gaussian membership functions to quantify the degree of every factor in the decision-making system and the multilevel gray relation to determine the weight of each parameter on stimulation effect. Finally through fuzzy arithmetic operator between multilevel weights and fuzzy evaluation matrix, score, rank, the reservoir quality, and predicted production will be gotten. Result of this new method shows that the evaluation of the production coincidence rate reaches 80%, which provides a new way for fractured gas reservoir evaluation.

A Generalized Compositional Approach for Reservoir Simulation

1983 ◽  
Vol 23 (05) ◽  
pp. 727-742 ◽  
Author(s):  
Larry C. Young ◽  
Robert E. Stephenson
Keyword(s):  
Enhanced Recovery ◽  
Gas Condensate ◽  
Reservoir Modeling ◽  
Pressure Equation ◽  
Compositional Modeling ◽  
Fluid Property ◽  
Black Oil ◽  
Fluid Properties ◽  
Newton Raphson ◽  
Raphson Method

A procedure for solving compositional model equations is described. The procedure is based on the Newton Raphson iteration method. The equations and unknowns in the algorithm are ordered in such a way that different fluid property correlations can be accommodated leadily. Three different correlations have been implemented with the method. These include simplified correlations as well as a Redlich-Kwong equation of state (EOS). The example problems considered area conventional waterflood problem,displacement of oil by CO, andthe displacement of a gas condensate by nitrogen. These examples illustrate the utility of the different fluid-property correlations. The computing times reported are at least as low as for other methods that are specialized for a narrower class of problems. Introduction Black-oil models are used to study conventional recovery techniques in reservoirs for which fluid properties can be expressed as a function of pressure and bubble-point pressure. Compositional models are used when either the pressure. Compositional models are used when either the in-place or injected fluid causes fluid properties to be dependent on composition also. Examples of problems generally requiring compositional models are primary production or injection processes (such as primary production or injection processes (such as nitrogen injection) into gas condensate and volatile oil reservoirs and (2) enhanced recovery from oil reservoirs by CO or enriched gas injection. With deeper drilling, the frequency of gas condensate and volatile oil reservoir discoveries is increasing. The drive to increase domestic oil production has increased the importance of enhanced recovery by gas injection. These two factors suggest an increased need for compositional reservoir modeling. Conventional reservoir modeling is also likely to remain important for some time. In the past, two separate simulators have been developed and maintained for studying these two classes of problems. This result was dictated by the fact that compositional models have generally required substantially greater computing time than black-oil models. This paper describes a compositional modeling approach paper describes a compositional modeling approach useful for simulating both black-oil and compositional problems. The approach is based on the use of explicit problems. The approach is based on the use of explicit flow coefficients. For compositional modeling, two basic methods of solution have been proposed. We call these methods "Newton-Raphson" and "non-Newton-Raphson" methods. These methods differ in the manner in which a pressure equation is formed. In the Newton-Raphson method the iterative technique specifies how the pressure equation is formed. In the non-Newton-Raphson method, the composition dependence of certain ten-ns is neglected to form the pressure equation. With the non-Newton-Raphson pressure equation. With the non-Newton-Raphson methods, three to eight iterations have been reported per time step. Our experience with the Newton-Raphson method indicates that one to three iterations per tune step normally is sufficient. In the present study a Newton-Raphson iteration sequence is used. The calculations are organized in a manner which is both efficient and for which different fluid property descriptions can be accommodated readily. Early compositional simulators were based on K-values that were expressed as a function of pressure and convergence pressure. A number of potential difficulties are inherent in this approach. More recently, cubic equations of state such as the Redlich-Kwong, or Peng-Robinson appear to be more popular for the correlation Peng-Robinson appear to be more popular for the correlation of fluid properties. SPEJ p. 727

scholarly journals A reservoir quality evaluation approach for tight sandstone reservoirs based on the gray correlation algorithm: A case study of the Chang 6 layer in the W area of the as oilfield, Ordos Basin

2021 ◽  
pp. 014459872199851
Author(s):  
Yuyang Liu ◽  
Xiaowei Zhang ◽  
Junfeng Shi ◽  
Wei Guo ◽  
Lixia Kang ◽  
...  
Keyword(s):  
Quality Evaluation ◽  
Comprehensive Evaluation ◽  
Ordos Basin ◽  
Reservoir Quality ◽  
Pore Throat ◽  
Tight Sandstone ◽  
Evaluation Approach ◽  
Correlation Algorithm ◽  
Gray Correlation ◽  
Sandstone Reservoir

As an important type of unconventional hydrocarbon, tight sandstone oil has great present and future resource potential. Reservoir quality evaluation is the basis of tight sandstone oil development. A comprehensive evaluation approach based on the gray correlation algorithm is established to effectively assess tight sandstone reservoir quality. Seven tight sandstone samples from the Chang 6 reservoir in the W area of the AS oilfield in the Ordos Basin are employed. First, the petrological and physical characteristics of the study area reservoir are briefly discussed through thin section observations, electron microscopy analysis, core physical property tests, and whole-rock and clay mineral content experiments. Second, the pore type, throat type and pore and throat combination characteristics are described from casting thin sections and scanning electron microscopy. Third, high-pressure mercury injection and nitrogen adsorption experiments are optimized to evaluate the characteristic parameters of pore throat distribution, micro- and nanopore throat frequency, permeability contribution and volume continuous distribution characteristics to quantitatively characterize the reservoir micro- and nanopores and throats. Then, the effective pore throat frequency specific gravity parameter of movable oil and the irreducible oil pore throat volume specific gravity parameter are introduced and combined with the reservoir physical properties, multipoint Brunauer-Emmett-Teller (BET) specific surface area, displacement pressure, maximum mercury saturation and mercury withdrawal efficiency parameters as the basic parameters for evaluation of tight sandstone reservoir quality. Finally, the weight coefficient of each parameter is calculated by the gray correlation method, and a reservoir comprehensive evaluation indicator (RCEI) is designed. The results show that the study area is dominated by types II and III tight sandstone reservoirs. In addition, the research method in this paper can be further extended to the evaluation of shale gas and other unconventional reservoirs after appropriate modification.

Study on Well Pattern Optimization of Tight Sandstone Gas Reservoir with the Strong Heterogeneity

2013 ◽  
Author(s):  
Ji Zhang ◽  
Tao Lu ◽  
Yuegang Li ◽  
Shuming Yu ◽  
Jingbu Li ◽  
...  
Keyword(s):  
Tight Sandstone ◽  
Gas Reservoir ◽  
Well Pattern ◽  
Well Pattern Optimization

Experiment on Mechanical Properties and Seepage Capability of Deep Tight Sandstone Under True-Triaxial Stresses Environment

2021 ◽  
Author(s):  
Jiaying Li ◽  
Chunyan Qi ◽  
Ye Gu ◽  
Yu Ye ◽  
Jie Zhao
Keyword(s):  
Mechanical Properties ◽  
In Situ Stress ◽  
Stress Sensitivity ◽  
Stress Conditions ◽  
Tight Sandstone ◽  
Gas Reservoir ◽  
True Triaxial ◽  
Strain Behavior ◽  
Triaxial Stresses

Abstract The characteristics of seepage capability and rock strain during reservoir depletion are important for reservoir recovery, which would significantly influence production strategy optimization. The Cretaceous deep natural gas reservoirs in Keshen Gasfield in Tarim Basin are mainly buried over 5000 m, featuring with ultra-low permeability, developed natural fractures and complex in-situ stress states. However, there is no comprehensive study on the variation of mechanical properties and seepage capability of this gas reservoir under in-situ stress conditions and most studies on stress-sensitivity are conducted under conventional triaxial or uniaxial stress conditions, which cannot truly represent in-situ stress environment. In this work, Cretaceous tight sandstone in Keshen Gasfield was tested under true-triaxial stresses conditions by an advanced geophysical imaging true-triaxial testing system to study the stress-sensitivity and anisotropy of rock stress-strain behavior, porosity and permeability. Four groups of sandstone samples are prepared as the size of 80mm×80mm×80mm, three of which are artificially fractured with different angle (0°,15°，30°) to simulate hydraulic fracturing. The test results corresponding to different samples are compared to further reveal the influence of the fracture angle on rock mechanical properties and seepage capability. The samples are in elastic strain during reservoir depletion, showing an apparent correlation with fracture angles. The porosity decreases linearly with stress loading, where the decrease rate of effective porosity of fracture samples is significantly higher than that of intact samples. The permeabilities decrease exponentially and show significant anisotropy in different principal stress directions, especially in σH direction. The mechanical properties and seepage capability of deep tight sandstone are successfully tested under true-triaxial stresses conditions in this work, which reveals the stress-sensitivity of anisotropic permeability, porosity and stress-strain behavior during gas production. The testing results proposed in this paper provides an innovative method to analyse rock mechanical and petrophysical properties and has profound significance on exploration and development of tight gas reservoir.

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