Exploratory analysis of machine learning methods in predicting subsurface temperature and geothermal gradient of Northeastern United States

Geothermal Energy

Science – Society – Technology

Table 1 Statistical summary of important parameters after outlier removal

	Surface temperature	Depth	Corrected BHT	Heat flow
Unit	°C	m	°C	mW/m²
Mean	12.4	1154	37	49
std	1.8	459	13.2	13.4
min	8.8	43	10.2	0.2
25%	10.6	868	28.9	41.57
50%	12.1	1129	34.5	47.91
75%	14.3	1358	42.8	55.26
max	15.6	6541	146.9	130.21

Variable number	Name	Unit	Source	Description	Type
1	BHTCorr	°C	Well log report	Corrected bottom-hole temperature	Label
2	LatDegree	–	Well log report	Lat degree of the well's location	Feature
3	LongDegree	–	Well log report	Long degree of the well's location	Feature
4	MeasureDepth	M	Well log report	The depth where BHT is recorded	Feature
5	SurfTemp	°C	Annual average temperature	Surf temperature at the well's location	Feature
6 to 55	KH	W/(°K)	Approximated from the data reported in Correlation of Stratigraphic Units of North America (COSUNA)	Multiplication product of each geological layer's thickness with its corresponding thermal conductivity	Feature