EVALUATION OF THE COMBINATION OF FRACTURING AND GRAVEL PACKING (FRAC&PACK) JOBS FOR HIGH PERMEABILITY AND SOFT SAND STONE FORMATION WELL COMPLETION: DURI STEAM FLOOD FIELD CASE
<b>Abstract:<p align=\"justify\"> <br /> In DSF, sand production is associated with unconsolidated or loosely consolidated formations. The primary goal of Frac&Pack (FP) completion is to improve the well productivity and for sand control by combining the advantages...
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| Format: | Theses |
| Language: | Indonesia |
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| Online Access: | https://digilib.itb.ac.id/gdl/view/5035 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | <b>Abstract:<p align=\"justify\"> <br />
In DSF, sand production is associated with unconsolidated or loosely consolidated formations. The primary goal of Frac&Pack (FP) completion is to improve the well productivity and for sand control by combining the advantages of hydraulic fracturing and gravel packing.<p align=\"justify\"> <br />
The Frac&Pack is a combination of fracturing and gravel packing in one operation with a liner in place. The Tip Screen Out (TSO) design technique is used to ensure that proper fracture width and conductivity are adequate to effectively connect the reservoir to the well bore. The Frac and Pack job is finished with an annular sand pack between the wire wrapped screen and the cased hole.<p align=\"justify\"> <br />
The study concerns the fracture dimension, that is, fracture radius and width, and its effect to the well productivity. Using fracture pressure analysis, the actual executed fracture dimension can be estimated.<p align=\"justify\"> <br />
It is shown that the well productivity is related to the fracture dimension. The productivity of the well increased as the fracture radius increase.<p align=\"justify\"> <br />
It is also shown that the fracture dimensions from executions are different with design. First attempt to improve the actual fracture dimension is by finding any correlation of the fracture dimension to the parameters such as: permeability, sand thickness, temperature, injection rate, pad volume, sand concentration etc. However the result shows that there are not good correlations among them, so the statistical approach (t-Test and Genetic Algorithm) is applied.<p align=\"justify\"> <br />
The results from t-Test and confirm with the Genetic Algorithm shows that there are four parameter that have high impact to the fracture dimension, they are: proppant weight, fracture fluid efficiency, well temperature, and fracturing injection rate.<p align=\"justify\"> <br />
It is also shown the best condition for those four parameters that result good fracture dimension.<p align=\"justify\"> |
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