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s of mud losses. Such an analysis should be based on a mathematical model that describes the physical phenomenon and the mechanism under which flow within the fractures take places. [4] Lavrov and Tronvoll developed a number of theoretical models that considered mud losses into a deformable fracture of finite length. Fracture opening/closing was the major mechanism for losses or gains. [4]
There are two analytical models in the literature developed to evaluate fracture width from hydraulic mud losses, both of which assume that the fracture width can be regarded as a slot of constant width with mud propagating radially into the fracture. The models assume the validity of Poiseuille flow so the fracture permeability is related to the fracture width or hydraulic aperture of the fracture. A model developed by Sanfilippo is based on the pressure diffusivity equation and applies to radial flow of mud into a fracture predominately intersecting the wellbore. Lietard et al. also developed a model based on radial flow of a Bingham-plastic fluid into an unlimited-extension fracture. [4] This paper first tries to introduce different methods of mud loss analysis of wellbore fractures detection. Dynamic data was used then to investigate wellbore fracture network - or a single fracture - existence in a well of an Iranian field using a new mud loss analysis model and special type curves. The results are compared to well log results also.
2. Mud Loss Identification
The exposure of open natural fractures by the drilling bit produces a sudden decrease of the outlet mud flow rate. According to Dyke et al. losses through matrix permeability or into natural fractures can be distinguished by the characteristics of the loss. Losses through pores start slowly and gradually increase as drilling proceeds whereas losses into natural fractures show a rapid
initial increase in loss rate followed by a gradual decline in time. Such loss progressions with time give rise to the typical responses in the mud tank level as shown in Figure 1. The same loss evolution in time was detected when mud losses were recorded by the flowmeters thus allowing discriminating between single conductive fractures and porous matrix or intensely fractured zones both inducing very similar mud losses into the formation. Figure 2 shows typical electromagnetic flowmeter responses in the two cases. [2]
3. Analysis of Mud Losses
Determination and detection of fracture type based on mud loss profile and drilling parameters such as RPM, ROP and WOB is possible using two methods. Older methods focus on depth of mud loss invasion zone and so the time factor is ignored. More recent methods consider the drilling time elapsed to determine flow regime in fractures. So using diffusivity equation in porous formations and determination of permeability and fracture depth becomes possible.
3.1. Qualitative Analysis - Time based -
7KH DLP RI WKH DSSURDFK KHUH SURSRVHG LV WKH DWWHPSWV WR EHWWHU LGHQWLI\ WKH "WUXH" PXG ORVVHV to precisely locate the conductive events and their characterization in terms of severity and typology. A list of the drilling parameters required to perform the qualitative analysis in time domain is reported in the Table 1.
