OR/21/006 Lithology determination using log cut-off values - Revision history

Ajhil: /* Normalisation of well log data */

2021-05-26T10:01:47Z

Normalisation of well log data

← Older revision		Revision as of 11:01, 26 May 2021
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	𝐶𝑢𝑟𝑣𝑒<sub>𝑛𝑜𝑟𝑚</sub> = ( 𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒 − 𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒<sub>𝑚𝑖𝑛</sub> )<br>		𝐶𝑢𝑟𝑣𝑒<sub>𝑛𝑜𝑟𝑚</sub> = ( 𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒 − 𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒<sub>𝑚𝑖𝑛</sub> )<br>
	𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒<sub>𝑚𝑎𝑥</sub> − 𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒<sub>𝑚𝑖𝑛</sub>		𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒<sub>𝑚𝑎𝑥</sub> − 𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒<sub>𝑚𝑖𝑛</sub>

	An alternative approach involves selecting a reference well (Ref) from within the dataset under consideration. Curves values from other wells (Curve) are then stretched and squeezed to match the minimum and maximum values of the corresponding curve in the reference well. This approach is frequently applied to gamma-ray data (Shier, 2004).		An alternative approach involves selecting a reference well (Ref) from within the dataset under consideration. Curves values from other wells (Curve) are then stretched and squeezed to match the minimum and maximum values of the corresponding curve in the reference well. This approach is frequently applied to gamma-ray data (Shier, 2004).

Ajhil: /* Normalisation of well log data */

2021-05-26T10:01:25Z

Normalisation of well log data

← Older revision		Revision as of 11:01, 26 May 2021
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	𝐶𝑢𝑟𝑣𝑒<sub>𝑛𝑜𝑟𝑚</sub> = ( 𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒 − 𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒<sub>𝑚𝑖𝑛</sub> )<br>		𝐶𝑢𝑟𝑣𝑒<sub>𝑛𝑜𝑟𝑚</sub> = ( 𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒 − 𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒<sub>𝑚𝑖𝑛</sub> )<br>
	𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒<sub>𝑚𝑎𝑥</sub> − 𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒<sub>𝑚𝑖𝑛</sub>		𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒<sub>𝑚𝑎𝑥</sub> − 𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒<sub>𝑚𝑖𝑛</sub>

	An alternative approach involves selecting a reference well (Ref) from within the dataset under consideration. Curves values from other wells (Curve) are then stretched and squeezed to match the minimum and maximum values of the corresponding curve in the reference well. This approach is frequently applied to gamma-ray data (Shier, 2004).		An alternative approach involves selecting a reference well (Ref) from within the dataset under consideration. Curves values from other wells (Curve) are then stretched and squeezed to match the minimum and maximum values of the corresponding curve in the reference well. This approach is frequently applied to gamma-ray data (Shier, 2004).

Ajhil: /* Normalisation of well log data */

2021-05-26T10:00:42Z

Normalisation of well log data

← Older revision		Revision as of 11:00, 26 May 2021
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	There are a number of different approaches to log normalisation—Normalisation might be carried out by using a simple linear shift of the log curve. This applies particularly where data has been recorded in different units.		There are a number of different approaches to log normalisation—Normalisation might be carried out by using a simple linear shift of the log curve. This applies particularly where data has been recorded in different units.

	~~𝐶𝑢𝑟𝑣𝑒𝑛𝑜𝑟𝑚~~ = 𝐶𝑢𝑟𝑣𝑒 + 𝑆ℎ𝑖𝑓𝑡		𝐶𝑢𝑟𝑣𝑒<sub>𝑛𝑜𝑟𝑚</sub> = 𝐶𝑢𝑟𝑣𝑒 + 𝑆ℎ𝑖𝑓𝑡

	In unity-based normalisation curves are rescaled to the minimum and maximum values, bringing all the values within the range [0,1]. The output values are dimensionless and any reference to the original absolute magnitude of the log response is lost.		In unity-based normalisation curves are rescaled to the minimum and maximum values, bringing all the values within the range [0,1]. The output values are dimensionless and any reference to the original absolute magnitude of the log response is lost.


	~~𝐶𝑢𝑟𝑣𝑒𝑛𝑜𝑟𝑚~~ = ( 𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒 − 𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒<sub>𝑚𝑖𝑛</sub> )<br>		𝐶𝑢𝑟𝑣𝑒<sub>𝑛𝑜𝑟𝑚</sub> = ( 𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒 − 𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒<sub>𝑚𝑖𝑛</sub> )<br>
	𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒<sub>𝑚𝑎𝑥</sub> − 𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒<sub>𝑚𝑖𝑛</sub>		𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒<sub>𝑚𝑎𝑥</sub> − 𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒<sub>𝑚𝑖𝑛</sub>

	An alternative approach involves selecting a reference well (Ref) from within the dataset under consideration. Curves values from other wells (Curve) are then stretched and squeezed to match the minimum and maximum values of the corresponding curve in the reference well. This approach is frequently applied to gamma-ray data (Shier, 2004).		An alternative approach involves selecting a reference well (Ref) from within the dataset under consideration. Curves values from other wells (Curve) are then stretched and squeezed to match the minimum and maximum values of the corresponding curve in the reference well. This approach is frequently applied to gamma-ray data (Shier, 2004).

Ajhil: /* Normalisation of well log data */

2021-05-26T09:53:32Z

Normalisation of well log data

← Older revision		Revision as of 10:53, 26 May 2021
Line 82:		Line 82:


	𝐶𝑢𝑟𝑣𝑒𝑛𝑜𝑟𝑚 = ( 𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒 − ~~𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒𝑚𝑖𝑛~~ )		𝐶𝑢𝑟𝑣𝑒𝑛𝑜𝑟𝑚 = ( 𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒 − 𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒<sub>𝑚𝑖𝑛</sub> )<br>
	~~𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒𝑚𝑎𝑥~~ − ~~𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒𝑚𝑖𝑛~~		𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒<sub>𝑚𝑎𝑥</sub> − 𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒<sub>𝑚𝑖𝑛</sub>

	An alternative approach involves selecting a reference well (Ref) from within the dataset under consideration. Curves values from other wells (Curve) are then stretched and squeezed to match the minimum and maximum values of the corresponding curve in the reference well. This approach is frequently applied to gamma-ray data (Shier, 2004).		An alternative approach involves selecting a reference well (Ref) from within the dataset under consideration. Curves values from other wells (Curve) are then stretched and squeezed to match the minimum and maximum values of the corresponding curve in the reference well. This approach is frequently applied to gamma-ray data (Shier, 2004).

Ajhil: /* Normalisation of well log data */

2021-05-26T09:44:48Z

Normalisation of well log data

← Older revision		Revision as of 10:44, 26 May 2021
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	𝐶𝑢𝑟𝑣𝑒𝑛𝑜𝑟𝑚		𝐶𝑢𝑟𝑣𝑒𝑛𝑜𝑟𝑚 = ( 𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒 − 𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒𝑚𝑖𝑛 )

	= ( 𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒 − 𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒𝑚𝑖𝑛 )
	𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒𝑚𝑎𝑥 − 𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒𝑚𝑖𝑛		𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒𝑚𝑎𝑥 − 𝐶𝑢𝑟𝑣𝑒𝑉𝑎𝑙𝑢𝑒𝑚𝑖𝑛

Ajhil: /* Normalisation of well log data */

2021-05-26T09:44:24Z

Normalisation of well log data

← Older revision		Revision as of 10:44, 26 May 2021
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	𝐶𝑢𝑟𝑣𝑒𝑛𝑜𝑟𝑚 = 𝐶𝑢𝑟𝑣𝑒 + 𝑆ℎ𝑖𝑓𝑡		𝐶𝑢𝑟𝑣𝑒𝑛𝑜𝑟𝑚 = 𝐶𝑢𝑟𝑣𝑒 + 𝑆ℎ𝑖𝑓𝑡

	In unity-based normalisation curves are rescaled to the minimum and maximum values, bringing all the values within the range [0,1]. The output values are dimensionless and any reference to the original absolute magnitude of the log response is lost.		In unity-based normalisation curves are rescaled to the minimum and maximum values, bringing all the values within the range [0,1]. The output values are dimensionless and any reference to the original absolute magnitude of the log response is lost.

Ajhil: /* Required input data */

2021-05-26T09:39:24Z

Required input data

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	</center>		</center>

			The risks and uncertainties associated with cut-off analysis using sub-optimal input data can be greatly reduced by starting projects with as much background geological information as possible. This should include information on the expected number of lithologies, the likely proportion of each lithology within the stratigraphic interval of interest, their typical mineralogy (with particular regard to the presence of radiogenic minerals such as glauconite) and the expected range of bed thickness and other parameters of the stratal architecture. The source of this information might be from the well itself in the form of cuttings descriptions, short cored intervals or sidewall cores, or from image logs (optical, acoustic or resistivity). Additional information on the geological formation under consideration might come from regional understanding gained from outcrop descriptions and adjacent boreholes. Finally, a general understanding of the depositional system under investigation can help control and verify the types, stacking order and bed thickness of lithologies that are being generated by the applied cut-offs.

			==Normalisation of well log data==
			Normalisation of well log data is a routine process within petrophysical workflows and is used to correct for inconsistencies between wells in the distribution of values recorded by a log for a particular lithology (Shier, 2004<ref name="Shier 2004">SHIER, D E. 2004. Well Log Normalization: Methods and Guidelines. ''Petrophysics'', 45.3: 268–280.</ref>). These variations can arise for many different reasons such as incorrect tool calibrations, varying tool vintage and changes in downhole environmental conditions between wells.

			Some form of normalisation will be required in nearly all cases where cut-off analysis is attempted as a batch process. Exceptions might occur where a cluster of similarly drilled and constructed wells have been logged by one service company who have applied a consistent set of corrections and calibration procedures to the log data.

	The ~~risks and uncertainties associated with~~ cut-off ~~analysis using sub~~-~~optimal input data~~ can be ~~greatly reduced by starting projects with~~ as ~~much background geological information as possible. This should include information on the expected number of lithologies~~, ~~the likely proportion of each lithology within the stratigraphic interval of interest~~, ~~their typical mineralogy (with particular regard to the presence of radiogenic minerals such as glauconite)~~ and ~~the expected range of bed thickness and other parameters of the stratal architecture~~. ~~The source of this information might be from the well itself in the form of cuttings descriptions~~, ~~short cored intervals or sidewall cores~~, ~~or from image logs~~ (~~optical~~, ~~acoustic or resistivity~~). ~~Additional information on the geological formation under consideration~~ might ~~come from regional understanding gained from outcrop descriptions and adjacent boreholes. Finally,~~ a ~~general understanding~~ of the ~~depositional system under investigation can help control and verify the types, stacking order and bed thickness of lithologies that are being generated by the applied cut-offs~~.		The normalisation process is a re-scaling or re-calibration procedure so that all logs in the set under consideration are consistent. A defined set of cut-off values in one well should therefore generate the same lithological classification in another. Normalization is commonly applied to gamma-ray logs, but can also be applied to all logs that sample bulk rock properties such as neutron porosity, bulk density, sonic and spontaneous potential logs. Resistivity logs, which are heavily affected by dynamic fluid properties, are generally not normalized unless there is a sufficient reason to do so (Shier, 2004<ref name="Shier 2004"></ref>).

			There are a number of different approaches to log normalisation—Normalisation might be carried out by using a simple linear shift of the log curve. This applies particularly where data has been recorded in different units.

	~~3.3 NORMALISATION OF WELL LOG DATA~~
	Normalisation of well log data is a routine process within petrophysical workflows and is used to correct for inconsistencies between wells in the distribution of values recorded by a log for a particular lithology (Shier, 2004). These variations can arise for many different reasons such as

	~~incorrect tool calibrations, varying tool vintage and changes in downhole environmental conditions between wells.~~
	Some form of normalisation will be required in nearly all cases where cut-off analysis is attempted as a batch process. Exceptions might occur where a cluster of similarly drilled and constructed wells have been logged by one service company who have applied a consistent set of corrections and calibration procedures to the log data.
	The normalisation process is a re-scaling or re-calibration procedure so that all logs in the set under consideration are consistent. A defined set of cut-off values in one well should therefore generate the same lithological classification in another. Normalization is commonly applied to gamma-ray logs, but can also be applied to all logs that sample bulk rock properties such as neutron porosity, bulk density, sonic and spontaneous potential logs. Resistivity logs, which are heavily affected by dynamic fluid properties, are generally not normalized unless there is a sufficient reason to do so (Shier, 2004).
	~~There are a number of different approaches to log normalisation –~~
	~~Normalisation might be carried out by using a simple linear shift of the log curve. This applies particularly where data has been recorded in different units.~~
	𝐶𝑢𝑟𝑣𝑒𝑛𝑜𝑟𝑚 = 𝐶𝑢𝑟𝑣𝑒 + 𝑆ℎ𝑖𝑓𝑡		𝐶𝑢𝑟𝑣𝑒𝑛𝑜𝑟𝑚 = 𝐶𝑢𝑟𝑣𝑒 + 𝑆ℎ𝑖𝑓𝑡
	In unity-based normalisation curves are rescaled to the minimum and maximum values, bringing all the values within the range [0,1]. The output values are dimensionless and any reference to the original absolute magnitude of the log response is lost.		In unity-based normalisation curves are rescaled to the minimum and maximum values, bringing all the values within the range [0,1]. The output values are dimensionless and any reference to the original absolute magnitude of the log response is lost.

Ajhil: /* Required input data */

2021-05-26T09:36:32Z

Required input data

← Older revision		Revision as of 10:36, 26 May 2021
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	{\| class="wikitable"		{\| class="wikitable"
	<span id="Table 2"></span>		<span id="Table 2"></span>
	\|+ Table 2    Quality checklist for geophysical log data in ~~order to~~<br> avoid working with erroneous data.		\|+ Table 2    Quality checklist for geophysical log data in<br>order to avoid working with erroneous data.
	\| ! scope="col" style="width: 500px;" \| Mud resistivity properties (Rm, Rmf) and corresponding temperature reported		\| ! scope="col" style="width: 500px;" \| Mud resistivity properties (Rm, Rmf) and corresponding temperature reported
	\| ! scope="col" style="width: 50px;" \| ✔		\| ! scope="col" style="width: 50px;" \| ✔

Ajhil: /* Required input data */

2021-05-26T09:36:14Z

Required input data

← Older revision		Revision as of 10:36, 26 May 2021
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	{\| class="wikitable"		{\| class="wikitable"
	<span id="Table 2"></span>		<span id="Table 2"></span>
	\|+ Table 2    Quality checklist for geophysical log data in order to avoid working with erroneous data.		\|+ Table 2    Quality checklist for geophysical log data in order to<br> avoid working with erroneous data.
	\| ! scope="col" style="width: 500px;" \| Mud resistivity properties (Rm, Rmf) and corresponding temperature reported		\| ! scope="col" style="width: 500px;" \| Mud resistivity properties (Rm, Rmf) and corresponding temperature reported
	\| ! scope="col" style="width: 50px;" \| ✔		\| ! scope="col" style="width: 50px;" \| ✔

Ajhil: /* Required input data */

2021-05-26T09:35:54Z

Required input data

← Older revision		Revision as of 10:35, 26 May 2021
Line 52:		Line 52:
	<span id="Table 2"></span>		<span id="Table 2"></span>
	\|+ Table 2    Quality checklist for geophysical log data in order to avoid working with erroneous data.		\|+ Table 2    Quality checklist for geophysical log data in order to avoid working with erroneous data.
	\| ! scope="col" style="width: ~~400px~~;" \| Mud resistivity properties (Rm, Rmf) and corresponding temperature reported		\| ! scope="col" style="width: 500px;" \| Mud resistivity properties (Rm, Rmf) and corresponding temperature reported
	\| ! scope="col" style="width: 50px;" \| ✔		\| ! scope="col" style="width: 50px;" \| ✔
	\|-		\|-