A review of closed-loop reservoir management

The closed-loop reservoir management technique enables a dynamic and real-time optimal production schedule under the existing reservoir conditions to be achieved by adjusting the injection and production strategies. This is one of the most effective ways to exploit limited oil reserves more economically and efficiently. There are two steps in closed-loop reservoir management： automatic history matching and reservoir production opti- mization. Both of the steps are large-scale complicated optimization problems. This paper gives a general review of the two basic techniques in closed-loop reservoir man- agement; summarizes the applications of gradient-based algorithms, gradient-free algorithms, and artificial intelligence algorithms; analyzes the characteristics and application conditions of these optimization methods; and finally discusses the emphases and directions of future research on both automatic history matching and reservoir production optimization.

Analysis of petrophysical cutoffs of reservoir intervals with production capacity and with accumulation capacity in clastic reservoirs

Methodologies have been developed for calculating cutoffs of reservoir intervals with production capacity （RIPC） and reservoir intervals with accumulation capacity （RIAC） according to the types of pore throat structures and dynamic force by using data from petrophysical analysis, production tests and mercury injection. The data are from clastic reservoirs in the third member （Es3） and the fourth member （Es4） of the Shahejie Formation in the Shengtuo area on the North Slope of the Dongying Sag, Jiyang Depression, China. The method of calculating cutoffs of RIPC is summarized as follows： 1） determination of permeability cutoffs of RIPC; 2） classification of types of pore-throat structures according to mercury injection data and then relating porosity to permeability and determining the relationship between porosity and permeability according to each type of pore-throat structure; and 3） calculating porosity cutoffs of RIPC using established correlation between porosity and permeability according to the type of pore throat structure. The method of calculating cutoffs of RIAC includes： 1） establishing a functional relationship between oil-water interracial tension and formation temperature; 2） calculating limiting values of maximum connected pore-throat radii according to formation temperature and dynamic forces of each reservoir interval; 3） correlating permeability with maximum connected pore-throat radius and then obtaining permeability cutoffs of RIAC; and 4） calculating porosity cutoffs on the basis of permeability cutoffs according to specific correlations, suitable for the type of porethroat structure. The results of this study show that porosity and permeability cutoffs of clastic reservoirs decrease with depth. For a fixed permeability cutoff, the porosity cutoff of R1PC varies because the type of pore throat is different. At a fixed temperature, porosity and permeability cutoffs of RIAC decrease as dynamic force increases. For a fixed permeability cutoff of effective hydrocarbon accumulation, the porosity cutoff also varies with different types of pore throat.

Identifying and Evaluating of Oil Reservoir

The identification and evaluation of oil reservoir with logging data are one of most important ways in geologic logging services. For the last decades, with the further development of the oil & gas exploration, great advances have been achieved in techniques on the acquisition, processing and interpretative evaluation of logging data. How to identify fluid characteristics and evaluate the productivity in light oil reservoir (the crude density being between 0.74g/cm3 and 0.82g/cm3)has become one of the difficulties.With the establishment of the regional interpretation criterion of the study blocks, the optimized logging parameters that reflect the reservoir characteristics have been used to establish the chart for the interpretation of oil-water reservoir combining with well logging parameters. Then, to begin with geologic reserves of crude in single well, we establish evaluation criterion for productivity in oil reservoir with determining lower limit value of the reservoir and applying the relationship between chart parameters. The techniques are verified in production and get better effect.On the basis of the reservoir characteristics analysis of both basin A and B, We established the evaluation method of static productivity on light oil reservoir with getting quantitative evaluation parameters after quantitatively evaluating the date of core, pyrolysis chromatogram and gas chromatogram. It provides new technique 7 for new well interpretation and old well review, as well as evidence for project.design of well testing.

Prediction of rock brittleness using nondestructive methods for hard rock tunneling

Sand production is an undesired phenomenon occurring in unconsolidated formations due to shear failure and hydrodynamic forces. There have been many approaches developed to predict sand production and prevent it by changing drilling or production strategies. However, assumptions involved in these approaches have limited their applications to very specific scenarios. In this paper, an elliptical model based on the borehole shape is presented to predict the volume of sand produced during the drilling and depletion stages of oil and gas reservoirs. A shape factor parameter is introduced to estimate the changes in the geometry of the borehole as a result of shear failure. A carbonate reservoir from the south of Iran with a solid production history is used to show the application of the developed methodology. Deriving mathematical equations for determination of the shape factor based on different failure criteria indicate that the effect of the intermediate principal stress should be taken into account to achieve an accurate result. However, it should be noticed that the methodology presented can only be used when geomechanical parameters are accurately estimated prior to the production stage when using wells and field data.